AIMS, HYPOTHESES AND HOW TO WRITE THEM
WHY DO WE HAVE AIMS AND HYPOTHESES?
Aims and hypotheses in research serve as fundamental components that provide direction and structure to the study. They are like signposts that guide researchers along the path of investigation. The aims outline the overarching goals or purposes of the study, while the hypotheses propose specific predictions or explanations to be tested. Together, they help researchers stay focused, establish clear objectives, and frame the inquiry systematically and organised. Defining the scope and purpose of the research, aims, and hypotheses enables researchers to pursue meaningful inquiry and contribute to advancing knowledge in their field.
Imagine you're embarking on a research journey to understand the factors influencing human mate selection. You aim to uncover the underlying mechanisms that drive mate preferences and ultimately contribute to reproductive success.
Your aim, therefore, is to explore the relationship between specific traits and their perceived attractiveness in potential mates. You want to investigate whether evolutionary factors such as facial symmetry, body proportions, and even personality traits play a role in shaping mate preferences.
With this aim in mind, you formulate hypotheses to guide your investigation. For example:
Hypothesis 1: Potential mates will perceive individuals with symmetrical facial features as more attractive than those with asymmetrical features.
Hypothesis 2: Men will prefer female partners who exhibit signs of reproductive health and fertility, such as a waist-to-hip ratio of 0.7.
Hypothesis 3: Women will prioritize traits in potential mates that signal resource acquisition and provisioning abilities, such as socioeconomic status and ambition.
These hypotheses serve as your roadmap, outlining the specific predictions you aim to test in your research. They provide a clear direction for your investigation and guide you toward a deeper understanding of the evolutionary underpinnings of mate selection.
In summary, aims and hypotheses in psychology, much like in any field of research, work together to guide inquiry, shape investigations, and ultimately contribute to advancing knowledge in understanding human behaviour and cognition.
WHAT’S THE DIFFERENCE BETWEEN AIMS AND HYPOTHESES?
AIMS
The aims and hypotheses of a study serve distinct purposes in research.
Aims are typically articulated towards the conclusion of the introduction section of a research paper, following the review of psychological literature. Once the researcher has provided the background history of the study and justified its necessity, the subsequent step is to outline the study's aim explicitly. This entails explaining the study's intended investigation and serving as a guiding framework for the research. The aim is to offer a comprehensive overview of the research study or proposal, delineating the objectives and questions to be addressed.
AIMS IN SHORT:
The justification provided in the introduction should logically lead to the aims, which in turn should logically transition into a statement of the hypothesis(es).
A general prediction about what the researcher expects to happen at the start of an investigation/research.
The aims typically focus on the intended outcomes or contributions of the research to the existing body of knowledge in the field.
AIM VERSUS HYPOTHESIS EXAMPLE
Aim - Strange Situation: The Strange Situation was developed by Mary Ainsworth and aimed to investigate infants' attachment styles towards their caregivers. Specifically, the study explored how infants react when separated from and reunited with their primary caregivers in a controlled laboratory setting. Based on the infants ' behaviours during seven key events, this study sought to identify attachment patterns, such as secure, insecure-avoidant, and insecure-resistant.
Hypothesis- Strange Situation: " There will be a higher quality of attachment associated with more positive behaviours exhibited by infants and their primary caregivers across seven key areas."
EXAMPLE OF AN “AIMS”
“Studies indicate a significant distortion in how individuals perceive body shape within the general population, with a particular emphasis on females; most research was conducted 20 years ago on American undergraduates. The following study aims to determine if these body distortions exist today in 16-to 18-year-old female English students. It will investigate the relationship between perceived body size and ideal body size in females with no history of eating disorders.”
HYPOTHESES
Hypotheses are tentative propositions or educated guesses formulated to explain observed phenomena or answer specific research questions. In neuroscience, hypotheses are often constructed to propose relationships between variables, such as brain activity and behaviour, or the effects of certain interventions on neural processes.
Example: Hypothesis: Increased activation in the prefrontal cortex is associated with improved working memory performance in adults.
Explanation: This hypothesis suggests that there is a relationship between the level of activation in the prefrontal cortex, a brain region associated with executive functions like working memory, and the performance of working memory tasks in adults
IN SUMMARY:
Hypotheses are specific, testable predictions or statements that propose a relationship or difference between variables.
Hypotheses have testable, operationalised terms.
Hypotheses are derived from the study's aims and are formulated based on theoretical considerations, existing evidence, or logical reasoning.
They articulate the expected outcomes or results of the study and provide a basis for testing the research questions.
Hypotheses are often framed as if-then statements, where the independent variable is expected to affect the dependent variable.
They guide the research process by clearly focusing on data collection, analysis, and interpretation.
Hypotheses are typically stated after the aims, as they are more specific and detailed statements that stem from the broader research goals outlined in the aims.
EXAMPLES OF HYPOTHESES
NULL AND ALTERNATIVE HYPOTHESES
There are two types of hypotheses: The Alternative (sometimes called the Experimental Hypothesis) and the Null Hypothesis.
WHAT IS A NULL HYPOTHESIS?
POPPER'S INFLUENCE ON NULL AND ALTERNATIVE HYPOTHESES
Contrary to popular belief, in scientific research, the protocol is to reject the null hypothesis, not confirm the alternative hypothesis. Before Popper, the null hypothesis, as it is now commonly understood, did not have a defined place in scientific methodology.
The null hypothesis (HO) is the foundational element in scientific experimentation. It represents the default assumption that there is no effect or difference in what is being studied. It is formulated in a way that can be potentially refuted. When deciding whether your research has worked, the scientific language is to accept or reject the null hypothesis and not to accept or reject the alternative hypothesis. This seemingly inconsequential rule demonstrates that the research in question is genuinely scientific as it is capable of having a null hypothesis, e.g., being refuted, unlike, for example, pseudoscientific theories like Freud's, which are incapable of being falsified. For instance, it cannot be refuted that a person has unconscious biases.
The null hypothesis states no effect or difference in what is being studied. It is formulated in a way that can be potentially refuted. For instance, consider the humorous hypothesis: "Baked beans cause naughtiness." This example illustrates how the null hypothesis can be tested and potentially disputed. However, if a hypothesis is theoretically impossible to disprove, such as the non-existence of ghosts, it may not be possible to formulate a null hypothesis, rendering the research unscientific.
Predicting nothing will happen is the opposite of your alternative/experimental hypothesis.
For example Null Hypothesis (H0):
“There is no difference between the perceived current body size of 16-18-year-old female students and their ideal body size as selected on a body shape scale.
"There is no significant relationship between the consumption of cheese before bedtime and the frequency or intensity of nightmares in individuals."
WHAT IS AN ALTERNATIVE HYPOTHESIS?
The alternative hypothesis suggests an effect or difference in the phenomenon under investigation and serves as the basis for comparison against the null hypothesis.
The term "Alternative Hypothesis" (H1) was coined to underscore its role as an alternative explanation to the null hypothesis. In scientific inquiry, the null hypothesis is pivotal as it can be either accepted or rejected based on empirical evidence, making it a fundamental aspect of hypothesis testing.
It is imperative for all research endeavors to incorporate an alternative hypothesis as it acknowledges the possibility that observed correlations or differences in conditions may not be solely attributable to chance, which the null hypothesis cannot ascertain. Interestingly, some psychologists interchangeably refer to the alternative hypothesis as an experimental hypothesis, though the latter term is specifically reserved for studies involving true experimental designs. Nonetheless, conceptually, both terms represent hypotheses that deviate from the null.
Alternative hypotheses are applicable across a spectrum of research contexts, encompassing both non-experimental studies and experiments, such as correlations and content analysis. They encompass both directional (1-tailed) and non-directional (2-tailed) hypotheses and are structured differently from experimental hypotheses.
Alternative Hypothesis (H1 or HA).: "The consumption of cheese before bedtime is associated with an increase in the frequency and intensity of nightmares in individuals."
In this alternative hypothesis, it is suggested that there is a specific relationship between eating cheese before bedtime and experiencing more frequent and intense nightmares. It proposes a cause-and-effect connection between the two variables.
On the other hand, the null hypothesis suggests no meaningful connection exists between eating cheese before bedtime and the occurrence or intensity of nightmares. It essentially states that any observed differences in nightmares are due to chance and unrelated to cheese consumption.
EXPERIMENTAL AND ALTERNATIVE HYPOTHESES
The alternative hypothesis suggests an effect or difference in the phenomenon under investigation and serves as the basis for comparison against the null hypothesis.
The term "Alternative Hypothesis" (H1) was coined to underscore its role as an alternative explanation to the null hypothesis. In scientific inquiry, the null hypothesis is pivotal as it can be accepted or rejected based on empirical evidence, making it a fundamental aspect of hypothesis testing.
All research endeavours must incorporate an alternative hypothesis as it acknowledges the possibility that observed correlations or differences in conditions may not be solely attributable to chance, which the null hypothesis cannot ascertain. Interestingly, some psychologists interchangeably refer to the alternative hypothesis as an experimental hypothesis, though the latter term is reserved explicitly for studies involving true experimental designs. Nonetheless, conceptually, both terms represent hypotheses that deviate from the null.
Alternative hypotheses are applicable across a spectrum of research contexts, encompassing both non-experimental studies and experiments, such as correlations and content analysis. They encompass directional (1-tailed) and non-directional (2-tailed) hypotheses and are structured differently from experimental hypotheses.
WHAT ARE DIRECTIONAL OR ONE-TAILED HYPOTHESES?
Hypotheses may take two forms: directional (1-tailed) and non-directional (2-tailed).
For directional experimental hypotheses, they propose a specific direction of the effect or relationship between variables. This is typically utilised in scenarios where researchers expect the outcome based on prior knowledge or theory. In other words, a hypothesis predicts which condition (IV) will do better or worse. In other words, it predicts one direction (tail) in which the results should occur.
Examples: ' Participants in the jogging condition will rate photographs of the opposite sex higher than participants in the non-jogging condition.’
Participants in the jogging condition will rate photographs of the opposite sex higher than participants in the non-jogging condition.
If Correlational, a directional hypothesis will predict a specific direction, e.g., negative or positive.
Example: ' There will be a positive correlation between the 4D and 2D finger ratio and Bateman’s risk-taking questionnaire scores.’
If a correlation does not specify if the outcome is considered to be positive or negative, then it is a non-directional hypothesis.
Directional quasi-experimental hypotheses propose a specific direction of the effect of participant differences on the dependent variable (DV) based on prior knowledge or theory.
Example: “Female participants will have higher IQs than male participants.”
WHAT ARE NON-DIRECTIONAL OR TWO-TAILED HYPOTHESES?
On the other hand, non-directional experimental hypotheses suggest a relationship or effect between variables, but they do not specify the direction of this effect. This is often used when researchers have no specific expectations regarding the outcome.
A hypothesis that does not predict which condition will do better or worse only states there will be differences in conditions (the IV). ¬ ® Example:
¬ ‘There will be a difference in the ratings of photographs of the opposite sex made by Participants in the jogging condition and participants in the non-jogging condition.’
Similarly, hypotheses may be non-directional in quasi-experimental designs where participant differences are independent variables (IV).
Non-directional quasi-experimental hypotheses, like their experimental counterparts, suggest a relationship between participant differences and the DV without specifying the direction of this relationship.
UNDERSTANDING HYPOTHESES:
Experimental hypotheses are for experimental research and should contain the word "difference" if applicable in their hypotheses (e.g., "There will be a difference between participants in the cheese condition and the non-cheese condition in the number of nightmares they experience").
Quasi-designs should also include the word "difference" in the hypotheses (e.g., "There will be a difference between French participants and English participants in the number of nightmares they experience.”
Alternative hypotheses are for all types of research, but they are usually used in non-experimental. research
For non-experimental research other than correlations, the word "association should be included in their hypotheses. (e.g., "There will be an association between variables advertised in Lonely Heart advertisements for females").
For correlations, include the words "correlation," "link," or "relationship" in the hypothesis (e.g., "There is a relationship between smartphone usage and lower attention span").
For all non-experimental research other than correlations, use the word "association" (e.g., "There will be an association between variables advertised in Lonely Heart advertisements for females")
TESTS OF DIFFERENCE HYPOTHESES
Tests of difference hypotheses are commonly used in experiments,e.g., those that compare the effects of different conditions or treatments on an outcome variable. They are also used in quasi-experiments,where the aim is to test differences between participants.
Experimental hypotheses are for experimental research and should contain the word "difference" if applicable (e.g., "There will be a difference between participants in the cheese condition and the non-cheese condition in the number of nightmares they experience").
Experimental hypothesis - directional (1 tailed) for ”true experiments”, e.g., laboratory and field
Experimental hypothesis - non-directional (2-tailed) for ”true experiments”, e.g., laboratory and field
Quasi-experimental hypothesis - directional (1 tailed) for experiments where the participant’s differences are the IV.
Quasi-experimental hypothesis - non-directional (2-tailed) for experiments where the participant’s differences are the IV.
TESTS OF ASSOCIATION HYPOTHESES
Non-experimental directional (1 tailed) for observations, questionnaire/surveys, interviews and case studies
Non-experimental, non-directional (2-tailed) for observations, questionnaire/surveys, interviews and case studies
TESTS OF CORRELATION HYPOTHESES
Correlations directional (1-tailed), e.g., positive correlations and negative correlations.
Correlations are non-directional (2-tailed), e.g., just predicting a correlation but not a direction, e.g., it could be either negative or positive.
Writing Experimental Alternative Hypotheses
These are for all experiments: Laboratory, Field, Quasi and Natural. Experimental Hypotheses include directional (1 tailed) and non-directional (2 tailed hypotheses).
HOW TO WRITE A HYPOTHESES
GENERAL STUFF ABOUT WRITING HYPOTHESES
TERMINOLOGY USAGE:
Always refer to individuals as "participants" unless studying non-human animals.
Use "male" and "female" instead of other terms like "man," "woman," "boy," or "girl."
OPERATIONALISATION OF VARIABLES:
Operationalise the independent variable (IV) by specifying how it will be measured or manipulated. For example, if studying the perception of age, indicate the age range (e.g., "Participants aged 18-19" to avoid subjective terms like "child" or "old").
Similarly, operationalise the dependent variable (DV) by stating how it will be measured or assessed. For instance, if studying intelligence, operationalise it as "participants' scores on a standardised IQ test."
Know the difference between experimental and alternative hypotheses. Alternative hypotheses are formulated in distinct ways to accommodate the requirements of diverse research methodologies.
You always write a null hypothesis.
HYPOTHEIS FORMULATION
The hypothesis must be worded precisely (called operationalised). A hypothesis such as:
‘Younger people have better memories than older people’ is too imprecise. What age groups are being tested?
The initial hypothesis, "Younger people have better memories than older people," lacks specificity. It's essential to specify the age groups being tested, the type of memory being assessed (short-term or long-term memory), and the metric used to determine "better" memory.
Candidates should ensure that the hypothesis (es) is unambiguous and understandable to someone who has not yet read the rest of the report.
A revised operationalised hypothesis could be:
Participants aged between 16 -25 will recall more digits from a standardised memory test than participants aged between 26- 35.
This hypothesis outlines the age groups, specifies the type of memory (short-term memory), and clarifies the measure of memory performance (number of digits recalled).
WRITING THE EXPERIMENTAL HYPOTHESES
GUIDE FOR WRITING ‘DIRECTIONAL OR ONE-TAILED EXPERIMENTAL HYPOTHESES.
There are many ways to write directional hypotheses; you'll adopt your version once you find your feet.
To write a directional or one-tailed experimental hypothesis, follow these steps using the following hypothesis as an example: "Participants in the cheese condition will have more nightmares than participants in the non-cheese condition."
STEP ONE: Identify the First IV/Condition
Begin with "Participants in the………… followed by the first condition. Example: "Participants in the cheese condition..."
"Participants in the cheese condition will have more nightmares than participants in the non-cheese condition."
STEP TWO: State the Expected Outcome:
Express what you predict will happen about the first IV/Condition. Use terms like "higher," "lower," "more," "less," "better," or "worse" to indicate the direction of the effect. Example: "...will have more."
"Participants in the cheese condition will have more nightmares than participants in the non-cheese condition."
STEP THREE: Operationalise the DV:
Clearly define the dependent variable (DV) and how it will be measured or assessed. Example: "...nightmares."
"Participants in the cheese condition will have more nightmares than participants in the non-cheese condition."
STEP THREE: Identify the Second IV/Condition: EXAMPLE: non-cheese condition
After stating the operationalized DV Example, mention the second condition: "...will have more nightmares..."Examples:
“Participants in the cheese condition will have more nightmares than participants in the non-cheese condition.”
GUIDE FOR WRITING ‘DIRECTIONAL OR ONE-TAILED QUASI-EXPERIMENTS
Remember you are testing the difference between two groups of participants here. So, the groups are different somehow (age, gender, intelligence, birth order, etc.). Why would you test the difference between two groups if they were not different?
The two groups will be tested on the same thing, so only one condition exists. We are not so much interested in what the two groups are doing; we are more interested in the difference between how the two groups perform against each other—for example, Blind participants and sighted participants and their hearing ability. The two groups of participants are the IV.
There are many ways to write non-directional hypotheses; you'll adopt your version once you find your feet.
To write a directional or one-tailed experimental hypothesis for quasi-designs, follow these steps using the following hypothesis as an example: “Participants from Nigeria 2) will have lower scores 3) on a body shape questionnaire 4) than participants from the UK”.
STEP ONE: Always start with ‘Participants who are (then state what is different from them to the other group, for example, male; female, aged 40-60; from Nigeria, etc.…………).
“Participants from Nigeria will have lower scores on a body shape questionnaire than participants from the UK”.
STEP TWO: State what you think will happen, e.g., if they score higher/lower, prefer more/less, better/worse, etc. What is your prediction?
“Participants from Nigeria will have lower scores on a body shape questionnaire 4) than participants from the UK”.
STEP THREE: State the OPERATIONALISED variable.
“Participants from Nigeria will have lower scores on a body shape questionnaire than participants from the UK”.
STEP FOUR: Always finish with the other set of participants (then state what is different from them to the other group, for example, male, female, aged 40-60; from Nigeria, etc.).
“Participants from Nigeria will have lower scores on a body shape questionnaire than participants from the UK”.
Examples:
Participants from Nigeria will have lower scores on a body shape questionnaire 4) than participants from the UK.
Participants who are male will rate photographs of the opposite sex higher than participants who are female.
Green participants will recall more digits from a standardised memory test than participants who are yellow.
Participants who came to live in the UK after the age of 18 will have lower scores on the Television addiction questionnaire than participants who were born in the UK (1 tail).
GUIDE FOR WRITING ‘NON-DIRECTIONAL OR TWO-TAILED EXPERIMENTAL HYPOTHESES.
There are many ways to write non-directional hypotheses; you'll adopt your version once you find your feet.
To write a non-directional or two-tailed experimental hypothesis, follow these steps using the following hypothesis as an example: "There will be a difference between participants in the cheese condition and participants in the non-cheese condition and the number of nightmares they have.”
STEP ONE: Identify the First IV/Condition and state the Expected Outcome:
Always start with ‘There will be a difference as you are not predicting a direction or tail, only non-similar results.
"There will be a difference between participants in the cheese condition and participants in the non-cheese condition and the number of nightmares they have.”
STEP TWO: Name the first condition
"There will be a difference between participants in the cheese condition and participants in the non-cheese condition and the number of nightmares they have.”
STEP TWO: Identify the Second IV/Condition: EXAMPLE: non-cheese condition
"There will be a difference between participants in the cheese condition and participants in the non-cheese condition and the number of nightmares they have.”
STEP THREE: Operationalise the DV:
Clearly define the dependent variable (DV) and how it will be measured or assessed. Example: "...nightmares."
"There will be a difference between participants in the cheese condition and participants in the non-cheese condition and the number of nightmares they have.”
GUIDE FOR WRITING ‘NON-DIRECTIONAL OR TWO-TAILED QUASI-EXPERIMENTS
Remember you are testing the difference between two groups of participants here. So, the groups are different somehow (age, gender, intelligence, birth order, etc.). Why would you test the difference between two groups if they were not different?
The two groups will be tested on the same thing, so only one condition exists. We are not so much interested in what the two groups are doing; we are more interested in the difference between how the two groups perform against each other—for example, males and females and driving ability. The two groups of participants are the IV.
To write a non-directional or two-tailed experimental hypothesis for quasi-designs, follow these steps using the following hypothesis as an example: “There will be a difference between male participants’ scores on a standardised anxiety test and female participants’ scores on a test (2-tailed).”
STEP ONE: The prediction part.
Begin with:” There will be a difference between….”
“There will be a difference between male participants’ scores on a standardised anxiety test and female participants’ scores on a test (2-tailed).”
STEP TWO: State what the difference will manifest as—e.g. scores, attitudes, preferences, etc.
“There will be a difference between male participants’ scores on a standardised anxiety test and female participants’ scores on a test (2-tailed).”
STEP THREE: State the operationalised DV.
State the first IV/condition. Always put ‘between participants in ……….condition and
“There will be a difference between male participants’ scores on a standardised anxiety test and female participants’ scores on a test (2-tailed).”
STEP four: State the second IV.
Always finish with ‘Participants in the other ……….condition.’
“There will be a difference between male participants’ scores on a standardised anxiety test and female participants’ scores on a test (2-tailed).”
Examples:
There will be a difference in the number of nightmares between participants in the cheese condition and in the non-cheese condition.
There will be a difference in the ratings of photographs of the opposite sex) between participants in the jogging condition and between participants in the non-jogging condition.
WRITING A NULL HYPOTHESES
Null Hypotheses are formulated in a manner akin to two-tailed hypotheses, with the inclusion of the term "no." Once you grasp the structure of writing alternative and experimental hypotheses, crafting null hypotheses becomes straightforward
’There will be no difference in the number of nightmares between participants in the cheese and non-cheese conditions.
There will be no difference in the ratings of photographs of the opposite sex between participants in the jogging condition and participants in the non-jogging condition.
There will be no difference between green and yellow participants’ scores on a standardized memory test.
There will be no correlation between height and drinking alcohol.
There will be no correlation between siblings’ SRSS scores.
There will be no association between female participants aged 25 – 35, who are more attracted to males with professional jobs, and female participants aged 18- 24, who are more attracted to looks.
WRITING FOR NON- EXPERIMENTAL HYPOTHESES
HYPOTHESES FOR TESTS OF CORRELATION
Use the word correlation or link or relationship in your hypothesis.
If one-tailed use either positive or negative
If two-tailed use just correlation
Examples below:
ONE-TAILED/DIRECTIONAL:
There will be a negative correlation between siblings’ scores on the Social Readjustment Rating Scale (SRSS) (1 tail).
There will be a positive correlation between high scores on a standardised happiness scale and high scores on the relationship satisfaction questionnaire (2 tail)
There will be a negative correlation between siblings' birth order and IQ.(1 tail)
There will be a positive correlation between siblings' birth order and IQ.(1 tail)
There will be a positive correlation between above 6ft and drinking alcohol excessively (1 tail)
TWO-TAILED/NON-DIRECTIONAL:
There will be a correlation between siblings’ scores on the Social Readjustment Rating Scale (SRSS) (2 tail).
There will be a correlation between high scores on a standardised happiness scale and high scores on relationship satisfaction questionnaire (2 Tail)
There will be a correlation between siblings' birth order and IQ.(2 Tail)
There will be a correlation between siblings’ scores on the Social Readjustment Rating Scale (SRSS) (1 tail).
There will be a correlation between above 6ft and drinking alcohol excessively (2 tail)
HYPOTHESES FOR TESTS OF ASSOCIATION
Tests of association cover interviews, questionnaire surveys, content analysis and observations.
Observation of girls and boys at play on the road and pavement.
Content analysis of males and females and what they advertise in Lonely Heart advertisements.
Questionnaire on older and younger females and types of males they are attracted to.
Remember to use the word association in your hypothesis, e.g., there will be an association between this variable and this variable.
Hypothesis examples:
DIRECTIONAL/ONE-TAILED
There will be a higher quality of attachment will be associated with more positive behaviours exhibited by infants and their primary caregivers across seven key areas."
Observation of girls and boys at play on the road and pavement. Hypothesis: Boys are likelier to play on the road than girls.
Content analysis of males and females and what they advertise in Lonely Heart advertisements. Hypothesis: Males will be more likely to advertise status than females in Lonely Heart advertisements.
Questionnaire on older and younger females and types of males they are attracted to. Hypothesis: Older females will be more likely to prefer males with professional jobs than younger females.
NON- NON-DIRECTIONAL/TWO-TAILED
"There will be a significant association between the quality of attachment and the behaviours exhibited by infants and their primary caregivers across seven key areas.
Observation of girls and boys at play on the road and pavement. Hypothesis: There will be an association between the gender of participants (girls vs. boys) and the location of play (road vs. pavement).
Content analysis of males and females and what they advertise in Lonely Heart advertisements. Hypothesis: There will be an association between the gender of participants (males vs. females) and the attributes advertised in Lonely Heart advertisements (looks vs. status).
Questionnaire on older and younger females and types of males they are attracted to. Hypothesis: There will be an association between the age group of female participants (older vs. younger) and the preferences for attributes in males (professional jobs vs. looks)
ACTIVITIES
OPERATIONALISING VARIABLES
Operationalise refers to precisely defining a variable so that it becomes unambiguous and objective. For instance, if two researchers are tasked with observing "naughtiness" on the playground, they might provide different interpretations because "naughtiness" is subjective
Try and operationalise the following:
Risk-taking
Depression:
Sexual attraction
Aggression: ·
Memory
Short-term memory
Intelligence
Attachment
Empathy
Stress
Anxiety
ANSWERS
There are no set answers in this question, check with me if you think you may have a good idea but it has not been listed.
Risk-taking:
Develop a risk-taking questionnaire or measure finger length ratio.
Question: How likely are you to engage in risky behaviour in the following scenarios? (Scale: 1-5)
Measure: Calculate the ratio between the length of the index and ring fingers.
Depression:
Administer a depression scale or conduct a clinical interview.
Question: Over the past two weeks, how often have you experienced symptoms such as sadness, loss of interest, or changes in appetite? (Scale: 0-3)
Measure: Conduct a structured clinical interview based on DSM criteria.
Sexual attraction:
Rate attractiveness from photographs or observe real-life interactions.
Question: On a scale from 1 to 10, how physically attractive do you find the person in the photograph?
Measure: Observe participants' eye movements when presented with images of different genders.
Aggression:
Conduct observations in playgrounds or use aggression scales.
Question: How often do you engage in physical or verbal aggression towards others? (Scale: 1-5)
Measure: Record the frequency of aggressive behaviours observed during playground observations.
Memory:
Administer memory tests or specifically use a digit span test for short-term memory.
Question: How many words can you recall from the list you just heard? (Immediate recall)
Measure: Use the number of correctly recalled digits in a sequence to measure short-term memory.
Intelligence:
Calculate an average of GCSE scores, ALIS scores, or IQ tests.
Question: What was your score on the standardized intelligence test?
Measure: Calculate the average score across multiple standardized tests.
Attachment:
Use the Strange Situation procedure or the Hazan and Shaver Love Quiz.
Question: How do you typically feel when separated from your primary caregiver? (Secure, insecure-avoidant, insecure-resistant)
Measure: Assess attachment style based on behaviours observed during the Strange Situation procedure.
Empathy:
Measure pupil dilation, use an empathy scale, or conduct experiments where participants stop to help an abandoned child.
Question: How much do you feel for others when they are experiencing strong emotions? (Scale: 1-7)
Measure: Record changes in pupil size while participants view emotionally charged images.
Stress:
Utilise the Social Readjustment Rating Scale (SRRS), daily Hassles Scale, or measure physiological responses like blood pressure and pupil dilation.
Question: How many stressful life events have you experienced over the past year? (Checklist)
Measure: Record changes in blood pressure and pupil dilation in response to stress-inducing stimuli.
Anxiety:
Measure heart rate, employ anxiety questionnaires, conduct Galvanic Skin Response tests, or test blood pressure.
Question: How anxious do you feel in social situations? (Scale: 1-10)
Measure: Record changes in heart rate during a stress-inducing task or social interaction
ACTIVITY: OPERATIONALISING VARIABLES
For each scenario below, operationalise the variables.
Adults with a mental illness will have impaired memory abilities.
Consumption of sugar-filled drinks will increase aggression in boys.
Girls who use social networking sites will have learning difficulties.
Stressed males will take more days off work.
ANSWERS
Adults with a mental illness will have impaired memory abilities.
Participants diagnosed with bipolar depression will have lower digit spans than participants without a mental illness.
Consumption of sugar-filled drinks will increase aggression in boys.
Male participants aged (5-10) who consume one can of Cola will commit more physically aggressive acts during their ten-minute morning break than male participants aged (5-10) who do not consume Cola.
Girls who use social networking sites will have learning difficulties.
Female participants (aged 12-17) who use social networking sites for more than 10 hours per week will have lower scores on the Stanford Binet intelligence test than participants who do not use social networking sites.
Stressed males will take more days off work.
There will be a positive correlation between high scores on the SRRS and the number of sick days in the preceding year for male participants aged 18-30.
Sometimes psychologists find it hard to operationalise variables themselves (or too unethical to operationalise – how could you operationalise risk-taking behaviour, for instance, without compromising a participant’s physical or psychological well-being?) and so rely on questionnaires, attitudes, tests, etc. These questionnaires, attitudes, and tests need to be standardised. You cannot just make one up! Standardized scales and tests are usually referred to by their specific name, e.g., The GAF scale, which measures a person’s everyday functioning. Standardised questionnaires/tests/scales (like IQ, ALIS, GCSE, A ‘level, Cattel’s personality test, etc.) are questionnaires or scales that psychologists have tested for validity and reliability.
QUESTIONS ON HYPOTHESES
What role do aims and hypotheses play in the research process?
Can you provide an example of an aim in research, specifically in evolutionary psychology?
Explain the purpose of formulating hypotheses in research.
What are the differences between aims and hypotheses?
How are aims typically presented in a research paper?
Provide an example of a hypothesis formulated in evolutionary psychology research.
What is the null hypothesis, and why is it important in scientific experimentation?
Explain the difference between a null hypothesis and an alternative hypothesis.
What is the significance of Popper's influence on null and alternative hypotheses?
Can you give an example of a null hypothesis in a research context?
Describe the characteristics of an alternative hypothesis.
How do directional (1-tailed) hypotheses differ from non-directional (2-tailed) hypotheses?
Provide an example of a directional hypothesis in an experimental context.
What is the purpose of tests of different hypotheses in experimental and quasi-experimental research?
Explain how to write hypotheses with the operationalisation of variables.
Why is it important for hypotheses to be worded precisely and unambiguously?
Write out the hypothesis for the following. Include 1, 2 tail and null
Participants either listen to music with aggressive or non-aggressive lyrics and then compare their scores on an aggression questionnaire.
2. Preference for masculine and feminine faces of men when females are ovulating or not ovulating.
3. The effect of TV on creativity (operationalise DV).
4. 2d and 4d finger length ratios and testosterone (operationalise as risk-taking, then operationalise variables further).
5. Who are the most conforming, males or females (operationalise variables)?
6. Gender and playing on the road or not (operationalise variables).
7. Older siblings and younger siblings and empathy (operationalise variables).
8. Physiological arousal or not (operationalise IV) and attraction to the opposite sex (operationalise DV).
ANSWERS
1a). Participants in the aggressive lyric condition will have higher scores on a standardised aggression test than participants in the non-aggressive lyric condition.
1b). There will be a difference in the scores on a standardised aggression test between participants in the aggressive and non-aggressive conditions.
1c). There will be no difference in the scores on the standardised aggression test between participants in the aggressive and non-aggressive lyric conditions.
2a). Female participants in the ovulation condition will have more preferences for masculine faces (BBC Masculine/Feminine face scale) than female participants in the non-ovulating condition.
2b). There will be a difference in a number of preferences for masculine and feminine faces (BBC Masculine/Feminine face scale) between female participants in the ovulating condition and female participants in the non-ovulating condition.
2c). There will be no difference in the preference for masculine and feminine faces (BBC Masculine/Feminine face scale) between female participants in the ovulating and non-ovulating conditions.
3a). Participants in the non-TV-watching condition will score higher on a standardised creativity test than participants in the TV watching condition
3b). There will be a difference in the scores on a standardised creativity test between participants in the watching TV condition and participants in the non-watching television condition.
3c). There will be no difference in the scores on a standardised creativity test between participants in the watching TV condition and participants in the non-watching television condition.
4a). There will be a correlation between participants’ 2d and 4d finger length ratios and scores on a risk-taking test.
4b). There will be a positive correlation between participants’ 2d and 4d finger length ratio and scores on a risk-taking test; the higher the ratio, the higher the risk test score. Or
4b). There will be a positive correlation between high’ 2d and 4d finger length ratios and high scores on a risk taking test.
4c). There will be no correlation between participants’ 2d and 4d finger length ratios and scores on a risk taking test.
5a). Male participants will score higher on a conformity questionnaire than female participants
5b). Male and female participants will differ in the scores on a conformity test.
5c). There will be no difference in the scores on a conformity test between male participants and female participants
6a). Male participants aged 5-7 will have one foot on the road more frequently than female participants aged 5-7
6b). There will be a difference in the frequency of having one foot on the road between male and female participants aged 5-7.
6c). There will be no difference in the frequency of having one foot on the road between male and female participants aged 5-7.
7a). There will be a negative correlation between older and younger siblings’ empathy scores.
7b). There will be a correlation between older and younger siblings’ empathy scores.
7c). There will be no correlation between older and younger siblings’ empathy scores.
8a). Participants in the jogging on the spot condition will rate photographs of the opposite sex higher in attractiveness than participants in the non-jogging on the spot condition.
8b). There will be a difference in the ratings of photographs of the opposite sex for attractiveness between participants in the jogging on-the-spot condition and participants in the non-jogging on-the-spot condition.
8c). There will be no difference in the ratings of photographs of the opposite sex for attractiveness between participants in the jogging on-the-spot condition and participants in the non-jogging on-the-spot condition.
