RM exam 2

Advantages of surveys

They measure attitudes, values, beliefs, ask about past behavior/life history, and provide large amounts of data in a short time.

Disadvantages of surveys

Data can be affected by participant's memory, knowledge, social desirability bias, misunderstandings of questions, and a lack of seriousness in responses.

Double barreled questions

A question that asks two things at once, e.g., 'Do you find using a cell phone to be convenient and time-saving?'

Leading questions

Questions structured to lead respondents to a particular answer, often using emotional or non-neutral language.

Negative wording

Questions containing negatives like 'no' or 'not' that can be confusing to respondents.

Response set

A tendency for respondents to consistently answer in a particular way, such as only choosing extreme points on a scale.

Yea saying and Nay saying

Patterns where respondents tend to agree or disagree with all items regardless of content.

Closed-ended questions

Questions that allow respondents to choose from a limited number of response alternatives.

Open-ended questions

Questions that allow respondents to answer freely, providing a greater variety of responses but are harder to analyze.

Rating scales

A method where respondents choose a numerical value on a predetermined scale, like strongly agree to disagree.

Sample

The set of individuals selected to participate in a study.

Population

The entire set of individuals of interest to a researcher.

Non-response bias

Occurs when survey participants are not representative of the larger group due to incomplete responses.

Convergent validity

The extent to which a measure correlates with other measures of the same construct.

Discriminant validity

The ability to distinguish between the construct being measured and other unrelated constructs.

Descriptive Research Questions

Aim to describe characteristics or trends, answering 'what,' 'who,' 'where,' and 'when.'

Predictive Research Questions

Focus on forecasting future outcomes based on existing data, answering 'what is likely to happen?'

Causal Research Questions

Seek to establish cause-and-effect relationships, answering 'why' and 'how.'

Attrition

The reduction in sample size due to participants not returning for a second round of testing.

Testing effects

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

Cronbach's alpha

A method for testing internal consistency by indicating the average correlation between scores on all pairs of items.

Positive correlation

As one variable increases, the other variable also increases.

Negative correlation

As one variable increases, the other variable decreases.

Raw data

Unprocessed data used in statistical tests such as t-tests and ANOVA.

Proportions

Ratios used with statistical techniques like chi-square and logistic regression.

Correlation vs causation

Correlation indicates that two variables move together but does not imply a direct cause, while causation confirms that one variable affects another.

Directionality problem

The issue where the causality may be the reverse of what is assumed.

Third-variable problem

When a third variable accounts for the relationship found between two other variables.

Restriction of range

When a computed correlation does not represent the full range of possible values, potentially distorting the perceived relationship.

Nonlinear relationship

When the relationship between variables is not linear; the strength of association is indicated by the Pearson correlation coefficient.

Outlier

An extreme score significantly larger or smaller than other values in the data set.

Correlation study

A research design that examines relationships between multiple dependent variables without manipulating any variables.

Pearson R statistic

A test determining whether a linear relationship exists between two variables measured on interval or ratio scales.

Scatterplot

A graph displaying the relationship between two dependent variables for a group of individuals.