Researxh

Question 1

What is a laboratory experiment in psychology?

Answer 1

A laboratory experiment is a study conducted in a highly controlled, artificial environment. The researcher manipulates the independent variable (IV) and controls extraneous variables as much as possible. This method has high internal validity but may have lower ecological validity because the setting is artificial and participants know they are being studied.

Question 2

What is a field experiment?

Answer 2

A field experiment is carried out in a natural, real-world environment rather than a lab. The researcher still manipulates the IV, but there is less control over extraneous variables. Field experiments tend to have higher ecological validity but can suffer from lower internal validity and ethical issues if participants are unaware of being studied.

Question 3

What is a natural experiment in psychological research?

Answer 3

In a natural experiment, the researcher does not manipulate the IV – it changes due to a naturally occurring event or pre-existing difference. Participants are not randomly allocated to conditions. This method allows study of variables that would be unethical or impractical to manipulate, but cause-and-effect conclusions are weaker.

Question 4

What is a quasi-experiment?

Answer 4

A quasi-experiment is a study that is ‘almost’ an experiment. The IV is not directly manipulated by the researcher but is a naturally existing difference between people or a condition that cannot be randomly assigned. This means there may be uncontrolled confounding variables, making it harder to establish cause and effect.

Question 5

What is an independent groups design in experiments?

Answer 5

In an independent groups design, different participants are used in each condition of the IV. This avoids order effects but participant variables could confound results. Researchers often use random allocation to assign participants to groups.

Question 6

What is a repeated measures design?

Answer 6

A repeated measures design uses the same participants in all conditions of the experiment. This controls for participant variables but introduces order effects and possible demand characteristics. Techniques like counterbalancing are used to reduce order effects.

Question 7

What is a matched pairs design?

Answer 7

In a matched pairs design, participants are paired up based on similar characteristics and then split so that one of each pair is in each condition. This reduces participant differences while avoiding direct order effects, but it can be time-consuming.

Question 8

What is an independent variable (IV) in an experiment?

Answer 8

The independent variable is the factor that the researcher manipulates or changes in an experiment to observe its effect. It’s the presumed cause.

Question 9

What is a dependent variable (DV)?

Answer 9

The dependent variable is the factor that is measured by the researcher in an experiment. It’s the presumed effect or outcome.

Question 10

What are extraneous variables?

Answer 10

Extraneous variables are any variables other than the IV that could potentially influence the DV if not controlled. They are basically ‘nuisance’ variables.

Question 11

What is a confounding variable, and how is it different from an extraneous variable?

Answer 11

A confounding variable is a variable other than the IV that has actually influenced the DV, systematically varying along with the IV. It muddles the results, making it unclear if the IV or the confound caused the effect.

Question 12

What does it mean to operationalise a variable?

Answer 12

Operationalisation means defining and expressing variables in practical, measurable terms. It ensures clarity so that the study can be replicated.

Question 13

What is a hypothesis in psychological research?

Answer 13

A hypothesis is a precise, testable statement predicting the outcome of a study. It states the expected relationship between variables.

Question 14

What is a null hypothesis?

Answer 14

The null hypothesis (H₀) is a statement of no effect or no difference, proposing that any observed effect is due to chance.

Question 15

What is an alternative hypothesis (also known as the experimental hypothesis)?

Answer 15

The alternative hypothesis (H₁) states that there is an effect or a difference. It is the opposite of the null hypothesis.

Question 16

What is a directional hypothesis and when would you use one?

Answer 16

A directional hypothesis specifies the expected direction of the effect. Researchers use it when previous research suggests the direction of an effect.

Question 17

What is a non-directional hypothesis and when is it appropriate?

Answer 17

A non-directional hypothesis predicts a difference or relationship but does not specify the direction of the effect. It is used when there isn’t strong prior evidence predicting the outcome’s direction.

Question 18

What is random sampling, and why is it used?

Answer 18

Random sampling is a technique where every member of the target population has an equal chance of being selected. It aims to obtain a sample that is unbiased and representative.

Question 19

What is opportunity sampling?

Answer 19

Opportunity sampling involves selecting participants who are readily available and willing at the time of the study. It is quick and convenient but often leads to a biased sample.

Question 20

What is volunteer sampling?

Answer 20

In volunteer sampling, participants volunteer themselves for the study. This method can reach motivated individuals but may produce a volunteer bias.

Question 21

What is systematic sampling?

Answer 21

Systematic sampling uses a predetermined system to select participants at regular intervals from a list of the population. It can be fairly representative but is only truly random if the list order is random.

Question 22

What is stratified sampling?

Answer 22

Stratified sampling involves categorising the population into subgroups and then randomly sampling from each subgroup in proportion to their frequency in the population. It enhances generalisability.

Question 23

What are the main ethical issues in psychological research?

Answer 23

The major ethical issues include informed consent, deception, protection from harm, privacy and confidentiality, and the right to withdraw.

Question 24

What is informed consent, and how can researchers ensure it?

Answer 24

Informed consent means participants should be fully informed about the research and any potential risks before agreeing to take part. Researchers provide a consent form explaining the study.

Question 25

How do researchers deal with deception in a study?

Answer 25

Deception occurs when participants are misled about the true purpose of the study. Researchers should avoid it if possible and debrief participants thoroughly afterward.

Question 26

What does protection from harm involve in research, and how is it maintained?

Answer 26

Protection from harm means ensuring participants do not experience physical or psychological harm beyond what they’d encounter in everyday life. Researchers maintain this by designing safe procedures and reminding participants they can stop at any time.

Question 27

What does protection from harm involve in research, and how is it maintained?

Answer 27

Protection from harm means researchers must ensure that participants do not experience physical or psychological harm beyond what they’d encounter in everyday life. This includes protecting them from undue stress, embarrassment, or pain. Researchers maintain this by designing safe procedures, screening out vulnerable participants, reminding them they can stop at any time, and monitoring for distress during the study. If unforeseen harm occurs, the researcher must terminate the procedure or provide intervention. After the study, debriefing can help alleviate any distress.

Question 28

Why are privacy and confidentiality important in psychological research, and how are they protected?

Answer 28

Privacy refers to a participant’s right to not reveal personal information or to not be observed in private situations. Confidentiality refers to the protection of participants’ data. To protect privacy, researchers should only observe in public settings and avoid collecting unnecessary personal details. To ensure confidentiality, researchers assign ID codes, store data securely, and report results in aggregate. Maintaining confidentiality encourages honest participation and upholds ethical standards.

Question 29

What is the right to withdraw in the context of research, and how do researchers implement it?

Answer 29

The right to withdraw means participants can stop participating in a study at any time without penalty and can withdraw their data after participation. Researchers implement this by informing participants at the start that they have this right and reminding them during the study. After the study, participants can request their data to be removed from the analysis.

Question 30

What is a thorough debriefing, and why is it important?

Answer 30

A debriefing is a post-study explanation given to participants, especially if any deception or psychological risk was involved. It informs participants of the study’s true aims, clarifies any deception, and provides additional information. Debriefing is important because it ensures participants leave in a similar state as they arrived, allows them to ask questions, and provides closure and support if needed.

Question 31

What is a pilot study and why is it used in research?

Answer 31

A pilot study is a small-scale trial run of a research design conducted before the main study. It tests procedures, materials, and measures to identify and fix problems. The purpose is to refine methods and improve the validity and reliability of the main study.

Question 32

What is peer review and what role does it play in psychological research?

Answer 32

Peer review is a process where experts evaluate a researcher’s work before publication or funding. It ensures scientific quality control by checking methodology, analysis, and conclusions. Peer review helps prevent flawed research from being disseminated and provides feedback for improvement.

Question 33

What is quantitative data in psychology?

Answer 33

Quantitative data are numerical data that can be counted or measured. Examples include test scores and reaction times. They allow for statistical analysis and are useful for identifying patterns and making comparisons.

Question 34

What is qualitative data?

Answer 34

Qualitative data are non-numerical, descriptive data that capture the quality of experiences. Examples include interview transcripts and diary entries. They provide rich detail and insight but can be more subjective to interpret.

Question 35

What is primary data?

Answer 35

Primary data is original data collected first-hand by the researcher for their study. It is tailored to the study's aims and allows the researcher control over quality, but can be time-consuming and costly.

Question 36

What is secondary data?

Answer 36

Secondary data is information already collected by someone else and reused by a researcher. It is often easier and cheaper to obtain but may raise issues of reliability or validity.

Question 37

What is the mean, and how is it calculated?

Answer 37

The mean is the arithmetic average of a set of numbers, calculated by adding all scores and dividing by the number of scores. It is informative for normal distributions but can be distorted by outliers.

Question 38

What is the median?

Answer 38

The median is the middle value in an ordered list of scores. It is useful because it is not affected by extreme scores as much as the mean.

Question 39

What is the mode?

Answer 39

The mode is the most frequently occurring score in a dataset. It can be used for categorical data and is simple to find, but may not always be informative.

Question 40

What is the range in a dataset, and how do you calculate it?

Answer 40

The range is the difference between the highest and lowest score in a dataset, calculated by subtracting the smallest value from the largest value. It gives a quick sense of variability but can be distorted by outliers.

Question 41

What is standard deviation (SD), and what does it tell us about data?

Answer 41

Standard deviation is a measure of dispersion that indicates how much individual scores differ from the mean. A low SD means scores are tightly clustered, while a high SD indicates greater variability.

Question 42

When is a bar chart used and what does it look like?

Answer 42

A bar chart displays discrete data or compares groups, consisting of separate bars where the length or height represents frequency or value. It is good for visualizing differences between categories.

Question 43

What is a histogram, and how is it different from a bar chart?

Answer 43

A histogram shows the distribution of continuous data, with bars touching each other. It represents ranges of values and is ideal for seeing the shape of the distribution, unlike bar charts which compare separate categories.

Question 44

What is a scattergram (scatter plot), and what kind of data is it used for?

Answer 44

A scattergram displays correlational data, showing the relationship between two continuous variables. Each point represents an individual’s scores on two variables, allowing for analysis of correlation.

Question 45

What is a normal distribution, and what are its key features?

Answer 45

A normal distribution is a symmetrical, bell-shaped curve where the mean, median, and mode are equal and located at the center. It is important for many statistical tests and describes how data is distributed.

Question 46

What is a skewed distribution?

Answer 46

A skewed distribution is one where data are not symmetrically distributed, causing one tail to be longer than the other. This affects the mean, median, and mode, indicating that data might be clustered on one end.

Question 47

What characterises a positively skewed distribution?

Answer 47

In a positively skewed distribution, the tail is longer on the right side. Most scores are low or moderate, with a few very high scores stretching out to the right. In a positive skew: Mode < Median < Mean. ## Footnote Example: A very difficult exam where most students scored low but a few scored very high would produce a positive skew.

Question 48

What characterises a negatively skewed distribution?

Answer 48

In a negatively skewed distribution, the tail is longer on the left side. Most scores are relatively high, with a few very low scores dragging out to the left. In a negative skew: Mean < Median < Mode. ## Footnote Example: An easy test where most students scored high but a few scored much lower would show a negative skew.

Question 49

What are levels of measurement, and why are they important?

Answer 49

Levels of measurement refer to the nature of the data scale and determine the appropriate statistical analysis. The main levels are nominal, ordinal, and interval. Knowing the level is important for selecting statistical tests and understanding mathematical operations. ## Footnote Nominal = categories, Ordinal = ordered ranks, Interval = numerical values with equal units.

Question 50

What is nominal data?

Answer 50

Nominal data is the lowest level of measurement, consisting of categories or names with no intrinsic order. Examples include blood types, favorite ice cream flavor, or yes/no responses. You can count frequencies and determine the mode, but cannot rank or perform arithmetic. ## Footnote Nominal data are often coded with numbers for convenience.

Question 51

What is ordinal data?

Answer 51

Ordinal data are ranked data where values can be placed in order, but intervals between values are not equal or known. Examples include finishing positions in a race or Likert scale responses. You can use medians and percentiles with ordinal data. ## Footnote It’s a step above nominal because it carries order information.

Question 52

What is interval data (and how is it different from ratio data)?

Answer 52

Interval data are numerical data on a scale with equal intervals but no true zero point. Classic examples include temperature in Celsius and IQ scores. Ratio data is interval data with a true zero, allowing for ratio statements. ## Footnote Examples of ratio data include height, weight, and time duration.

Question 53

What are the three main criteria for selecting an appropriate inferential statistical test in psychology?

Answer 53

The three main criteria are: 1. The aim of the analysis (test of difference or relationship), 2. The experimental design (independent or repeated measures), 3. The level of measurement of the data (nominal, ordinal, or interval/ratio).

Question 54

Which statistical test would you use for a study investigating a difference between two independent groups with nominal data?

Answer 54

The appropriate test is Chi-Square (χ²) test of association/independence. It examines whether the frequency distribution across categories differs between groups. ## Footnote Example: Comparing the proportion of people who improve vs. don’t improve between a therapy group and a control group.

Question 55

Which statistical test is used for a difference between two related sets of scores with nominal data?

Answer 55

The appropriate test is the Sign Test. It looks at the direction of change for each participant between two conditions. ## Footnote Example: Testing if people are more likely to choose 'yes' in Condition A vs. Condition B.

Question 56

Which statistical test should be used for a test of difference with an independent groups design and ordinal data?

Answer 56

You would use a Mann-Whitney U test. It compares the ranks of scores from two separate groups. ## Footnote Example: Comparing anxiety rank scores between a therapy group and a control group.

Question 57

Which statistical test is appropriate for a test of difference with a repeated measures design using ordinal data?

Answer 57

The Wilcoxon Signed-Rank test is used for a repeated measures design with ordinal or non-normally distributed interval data. ## Footnote Example: Testing if participants’ stress levels differ before and after a mindfulness course.

Question 58

What statistical test is used for a correlation study with ordinal data?

Answer 58

The appropriate test is Spearman’s Rank Order Correlation (Spearman’s rho). It calculates a coefficient indicating the strength and direction of the association. ## Footnote Example: Examining the correlation between people’s rank in extraversion and the number of close friends.

Question 59

What statistical test is used for a correlation with interval data?

Answer 59

You use Pearson’s Product-Moment Correlation. It measures the linear relationship between two continuous variables. ## Footnote Example: Correlating IQ scores and memory test scores.

Question 60

Which test would you use for a difference between two independent groups with interval data?

Answer 60

You use an Independent (Unrelated) t-test. It compares the means of two separate groups. ## Footnote Example: Comparing the mean memory test score of a group that slept 8 hours vs. a group that slept 4 hours.

Question 61

Which test is appropriate for a difference in a repeated measures design with interval data?

Answer 61

The appropriate test is a Related t-test (paired samples t-test). It looks at the mean difference between two sets of related scores. ## Footnote Example: Comparing participants’ mean anxiety score before and after therapy.

Question 62

What does it mean if a result is significant at p < 0.05?

Answer 62

It means the probability of the finding being due to chance is less than 5%. If the null hypothesis were true, there’s less than a 0.05 probability that the observed difference would occur. ## Footnote Researchers conventionally use 0.05 as the significance level.

Question 63

What is a Type I error in hypothesis testing?

Answer 63

A Type I error occurs when a researcher incorrectly rejects the null hypothesis when it is true. It’s a 'false positive'. The probability of a Type I error corresponds to the alpha level. ## Footnote Example: Saying a drug works when it actually does nothing.

Question 64

What is a Type II error in hypothesis testing?

Answer 64

A Type II error happens when a researcher fails to reject the null hypothesis when the alternative hypothesis is true. It’s a 'false negative'. The probability of a Type II error is denoted by beta (β). ## Footnote Example: Concluding a teaching method has no impact when it actually does.

Question 65

How does the significance level (alpha) relate to Type I and Type II errors?

Answer 65

The significance level (alpha) is the threshold for rejecting the null hypothesis. A lower alpha reduces Type I errors but increases Type II errors, while a higher alpha does the opposite. ## Footnote Typically, 0.05 is used as a compromise.

Question 66

What does a lower alpha (like 0.01) mean in hypothesis testing?

Answer 66

A lower alpha means you require stronger evidence to claim significance, reducing the risk of Type I errors but increasing the risk of Type II errors.

Question 67

What does a higher alpha (like 0.1) mean in hypothesis testing?

Answer 67

A higher alpha increases the risk of Type I errors (more false alarms) but reduces Type II errors (fewer misses).

Question 68

What is statistical power in research methods?

Answer 68

Statistical power is the probability that a test will correctly reject a false null hypothesis. It’s essentially 1 minus the probability of a Type II error (1 – β).

Question 69

What is a critical value in inferential statistics?

Answer 69

A critical value is a cutoff score that a test statistic must exceed for results to be declared statistically significant at a certain probability level.

Question 70

How do you use a critical values table to determine significance?

Answer 70

1. Choose the correct table for your statistical test. 2. Determine the degrees of freedom (df) or sample size (N). 3. Decide on one-tailed or two-tailed. 4. Find the critical value that matches your df at the chosen significance level. 5. Compare your calculated test statistic to the critical value.

Question 71

What does it mean if an observed value is greater than the critical value?

Answer 71

It means the result is statistically significant at that alpha level, leading to the rejection of the null hypothesis.

Question 72

What should a researcher conclude if a result is not significant?

Answer 72

The researcher fails to reject the null hypothesis, indicating there isn’t enough evidence to claim a real effect or difference.

Question 73

What is reliability in the context of research measures?

Answer 73

Reliability refers to the consistency or stability of a measure or study, yielding similar results upon repeated application.

Question 74

What is internal reliability?

Answer 74

Internal reliability assesses the consistency of a measure within itself, often evaluated using the split-half method or Cronbach’s alpha.

Question 75

What is external reliability?

Answer 75

External reliability refers to the consistency of a measure over time or across different occasions, typically assessed using the test-retest method.

Question 76

How can researchers improve reliability in their studies?

Answer 76

Strategies include standardisation of procedures, operationalising variables clearly, training observers, pilot testing, and using reliable measures.

Question 77

What is validity in research?

Answer 77

Validity refers to the accuracy of a measure or study, determining whether it measures what it intends to measure.

Question 78

What is internal validity?

Answer 78

Internal validity assesses whether the outcome was truly caused by the manipulated independent variable, free from confounding factors.

Question 79

What is external validity?

Answer 79

External validity refers to the extent to which study results can be generalised beyond the research itself.

Question 80

What are face validity and concurrent validity?

Answer 80

Face validity is the extent to which a measure appears to measure what it’s supposed to. Concurrent validity assesses how well a new measure correlates with an established measure.

Question 81

How can researchers improve the validity of their studies?

Answer 81

Improving validity involves controlling extraneous variables, using representative samples, ensuring good construct validity, and pilot testing instruments.

Question 82

What is a case study in psychological research?

Answer 82

A case study is an in-depth investigation of a single individual, group, or event, often using multiple methods to gather detailed information.

Question 83

What are some strengths and limitations of the case study method?

Answer 83

Strengths include detailed insights and hypothesis generation; limitations involve challenges in generalising findings to broader populations.

Question 84

What are some strengths and limitations of the case study method?

Answer 84

Strengths: Case studies yield a wealth of detailed information and can provide deep insights into phenomena that might be lost in a larger quantitative study. They can help generate hypotheses or illustrate how theories apply in real life. They’re particularly useful for studying unusual or unethical-to-create scenarios. Limitations: Findings from case studies lack generalisability because they focus on one (or a very few) instances. They also tend to be more subjective, and without controlled variables, it’s hard to establish causality.

Question 85

What is content analysis, and what is it used for in research?

Answer 85

Content analysis is a research technique for systematically analyzing qualitative materials by converting them into quantitative or categorical data. Researchers use it to study various materials, especially to find patterns or themes.

Question 86

How is a content analysis conducted?

Answer 86

The basic steps include: 1. Data Collection: Gather material to be analysed. 2. Coding System Development: Develop a coding frame for key themes. 3. Pilot Coding: Test the coding system on a subset of data. 4. Coding the Data: Tally instances that fit each code/category. 5. Analysis: Count frequencies and look for patterns.

Question 87

What is thematic analysis, and how does it relate to content analysis?

Answer 87

Thematic analysis is a method of identifying and analyzing patterns of meaning in qualitative data. It focuses on broader themes rather than just counting frequencies, aiming to capture rich descriptions of those themes.

Question 88

What is a meta-analysis in psychological research?

Answer 88

A meta-analysis is a technique where a researcher combines results from many different studies on the same topic to get an overall picture of the effect.

Question 89

What are the benefits of conducting a meta-analysis?

Answer 89

Benefits include increased power and more robust conclusions, resolving contradictions, generalisation across varied samples, and identification of moderating variables.