RM exam 2

Chapter 10 

1. Advantages and disadvantages of of surveys

• Advantages: Measure attitudes, values and beliefs, ask about past behavior/life history and can provide large amounts of data in short time 

• Disadvantages: Data are affected by participants memory, knowledge, social desirability bias, may misunderstand questions and may not take surveys seriously. 

2. Simplicity 

• Avoid technical terms; if necessary define prior to asking question 

3. Double barreled questions 

• A question that asks two things at once. Ex: do you find using a cell phone to be convenient and time saving? 

4. Leading questions

• A question that is written to lead people to respond in one way. May use emotional or non-neural terms. 

5. Negative wording 

• Avoid having negatives like “no”  and “not” in the question

6. Response set

• The tendency to consistently respond in a certain way. Use only the two extreme points of a scale, only midpoint, etc..

7. Yea saying and Nay saying 

• Respondents may have a response set to agree or disagree with all items. 

• How to solve = word questions so that agreement means different things

8. Closed ended questions & open ended questions 

• Closed: choose from a limited number of responses alternatives. Easy to analyze but limits responses. 

• Open: free to answer any way they like. Greater variety but difficult to analyze 

9. Rating scales 

• Choose a numerical value on a predetermined scale (strongly agree -5, disagree -1).

10. Number of alternatives on rating scale 

• Scales with between 4 and 7 options have the best reliability. 

• Odd number= neutral option 

• Even number= forced to lean in one direction 

11. Sequence of questions

• Most interesting and important questions first 

• Sensitive topics later 

• Demographic question last 

• Group questions by theme 

12. Sample, population 

• Sample: The set of individuals selected to participate in a study 

• Population: The entire set of individuals of interest to a researcher the individuals who actually complete a survey affects how well the results generalize to overall population 

13. Non-response bias 

• When a researcher sends out a survey to a sample, but the individuals who complete the survey are not representative of the entire group who was sent the survey. Ex: Survey about how much people like watching sports teams. (who is more likely to fill this out?) 

14. Convergent validity 

• The extent to which your measure correlates with other measures of the same construct. (criterion-related validity and concurrent validity, are similar to this)

15. Discriminant validity 

• Divergent validity; The measure should distinguish between the construct being measured and other unrelated constructs.

• E.g., a measure of extraversion should have no correlation with a measure of intelligence. (have participant dp both your measure and the “other” measure

16. Description, predictive and causal research questions 

• Descriptive Research Questions – These aim to describe characteristics, behaviors, or trends. They answer "what," "who," "where," and "when."

• Example: What are the most common leadership styles used in the workplace?

• Predictive Research Questions – These focus on forecasting future outcomes based on patterns or existing data. They answer "what is likely to happen?"

• Example: How does an employee's level of engagement predict their likelihood of staying with a company?

• Causal Research Questions – These seek to establish cause-and-effect relationships by determining whether one factor directly influences another. They answer "why" and "how."

• Example: How does transformational leadership impact employee productivity?

17. Attrition

• participants may not come back the second time, and the sample size is then reduced

18. Testing effects

• A measure of reliability based on the average correlations between pairs of items on a survey.

19. Split-half reliability 

• method of testing scores’ internal consistency that indicates if the scores are similar on different sets of questions on a survey that address similar topics

20. Cronbach's alpha 

• method of testing scores’ internal consistency that indicates the average correlation between scores on all pairs of items on a survey

Chapter 11 

21. Positive correlation, negative correlation 

• Pos- As one variable increases, the other one increases. Ex: blood pressure and stress

• Neg-as one variable increases the other decreases. Ex: screen time and exercise time 

22. Raw data vs proportions 

• Raw Data → Unprocessed; uses t-tests, ANOVA, coding

•  Proportions → Ratios; uses chi-square, logistic regression.

23. Correlation vs causation 

• Correlation → A relationship where two variables move together but don’t imply cause. (e.g., Ice cream sales and drowning rates both rise in summer.)

• Causation → One variable directly affects another. (e.g., Exercise reduces body fat.)

24. Directionality problem 

• Maybe the causality is the reverse of what we think. Ex; good reading causes higher self esteem.

25. Third-variable problem

• When a third variable accounts for the relationship you found between two variables. Ex: parental praise causes better reading ability and higher self esteem  

26. Restriction of range

• If a correlation is computed from scores that do not represent the full range of possible values = can make relationship look differently than it really is  

27. Nonlinear relationship 

• Pearson correlation coefficient (R ) indicates strength of the linear relationship between two variables. 

28. Outlier 

• An extreme score; a score that is substantially larger or smaller than the other values in the data set

29. Correlation study 

• a type of research design that examines the relationships between multiple dependent variables, without manipulating any of the variables

30. Pearson R statistic 

• A significance test used to determine whether a linear relationship exists between two variables measured on interval or ratio scales

31. Scatterplot 

• a graph showing the relationship between two dependent variables for a group of individuals