Lecture 10 PSYCH2018

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Questions and Answers

What does a Pearson's correlation coefficient of $0.409$ indicate about the relationship between the two variables being studied?

There is a strong positive correlation.

There is a moderate positive correlation. (correct)

There is no correlation.

There is a weak negative correlation.

If a study reports an $r$ value of $0.6$ and an $r^2$ value of $0.36$, what percentage of the variability in the predictive variable is due to other factors?

36%

54%

60%

64% (correct)

How can outliers affect the computation of Pearson's $r$ and $r^2$ in a dataset?

They have no effect on the calculation of correlation coefficients.

They always enhance the accuracy of the correlation.

They can dramatically distort the results and lead to possible Type I errors. (correct)

They only affect the regression line but not the correlation.

In the equation $Y = a + bX$, what does $Y$ represent?

The predicted value that is being estimated. Signup and view all the answers

What is the main purpose of regression analysis as mentioned in the content?

To estimate individual scores and the accuracy of those estimates. Signup and view all the answers

What is a key issue affecting the validity of survey research compared to other research methods?

Sampling bias Signup and view all the answers

Which of the following types of sampling involves selecting participants based on specific characteristics rather than at random?

Self-selection sampling Signup and view all the answers

In survey research, which question type allows respondents to provide their thoughts in their own words?

Open-ended questions Signup and view all the answers

What does a regression analysis aim to accomplish in the context of survey data?

Making predictions Signup and view all the answers

Which type of correlation indicates a direct relationship where an increase in one variable corresponds to an increase in another?

Positive correlation Signup and view all the answers

In the context of correlation, what challenge does the third variable problem pose?

It confuses the interpretation of causation Signup and view all the answers

What does the coefficient of determination ($r^2$) indicate in a regression analysis?

The variability accounted for by the model Signup and view all the answers

Which of the following factors differentiates mediators from moderators in the context of third variables in correlation studies?

Mediators explain the relationship, while moderators influence its strength. Signup and view all the answers

What is a key advantage of in-person interview surveys?

Comprehensive follow-up interactions Signup and view all the answers

Which type of survey question avoids both biased and leading wording?

How often do you use this technique? Signup and view all the answers

What does a positive correlation between study hours and GPA suggest?

Higher study hours are linked to higher GPAs Signup and view all the answers

In a scatterplot, what does an 'r' value of -1.00 represent?

Strong negative correlation Signup and view all the answers

What is typically the purpose of employing Likert scales in surveys?

To avoid response bias in questionnaires Signup and view all the answers

What does the moderate use of a 'Don't Know' alternative in surveys help to address?

Response bias Signup and view all the answers

When designing a survey, why should demographic questions be placed at the end?

To avoid biasing responses to main questions Signup and view all the answers

If a study finds a negative correlation between goof-off hours and GPA, what does this imply?

Increased goof-off hours lead to decreased GPA Signup and view all the answers

Which of the following is NOT a limitation of mailed written surveys?

Ease of scoring Signup and view all the answers

What is the range of correlation coefficients, and what does it indicate?

-1.00 to +1.00 indicates the strength of an association Signup and view all the answers

What does the slope (b) of a regression line indicate?

The impact of the predictor variable on the criterion variable Signup and view all the answers

Which scenario best describes a mediator variable?

It explains how one variable affects another through a third variable. Signup and view all the answers

In regression analysis, what do survey data typically provide?

Information primarily about attitudes and projected behaviors Signup and view all the answers

What problem arises from interpreting correlational results regarding the relationship between two variables?

The directionality problem between the variables Signup and view all the answers

When a regression analysis involves multiple predictor variables, it is referred to as:

Multiple regression Signup and view all the answers

Which aspect is essential when conducting surveys to ensure clear results?

Well-defined empirical questions Signup and view all the answers

What is one primary use of non-experimental research methods?

To analyze survey data and related ideas Signup and view all the answers

What is shared variance ($r^2$) used to measure in regression analysis?

The proportion of variance in the criterion variable explained by the predictors Signup and view all the answers

Study Notes

Chapter 9: Non-Experimental Design I: Survey Methods - Chapter Objectives

Sampling issues are more important in survey research than other psychological research.
Understanding the principles of good survey design is crucial.
Recognizing challenges in interpreting survey data is essential.
Knowing different methods for collecting survey data and their advantages/disadvantages is key.

Chapter Objectives (Page 2)

Three types of probability sampling, and when to use each, should be understood.
Identifying positive and negative bivariate correlations, and creating scatterplots to illustrate them.
Calculating and interpreting the coefficient of determination (r²).
Understanding how regression analysis makes predictions, differentiating between simple and multiple linear regression.

Chapter Objectives (Page 3)

Recognizing how directionality can impede the interpretation of correlations.
Understanding how cross-lagged panel studies can address directionality issues.
Understanding and controlling the third variable problem through partial correlation.
Differentiating between mediators and moderators, considering third variables in correlation.

Survey Research - Learning From History (Page 4)

Early survey research, including Darwin's work on facial expressions, and Galton's inquiry into scientific interests, highlight aspects like methodological issues and overly specific questions in survey design.
Early examples of survey research, such as Galton's and Hall's works, serve as historical contexts for understanding the development of psychological research, including survey methodologies.

Survey Research - Sampling Issues (Page 5)

Understand the difference between biased and representative samples in survey research.
Non-probability sampling vs. probability sampling (see Chapter 4).
Recognizing self-selection bias in surveys, using the example of the 1936 Literary Digest poll.
Understanding demand characteristics in surveys.
Surveys are used to assess psychological functioning, as well as beliefs, attitudes and so on.

Types of Survey Questions (Page 6)

Open-ended vs. closed-ended questions.
Use of Likert scales to avoid response bias.
Assessing memory and knowledge in surveys.
Use of "don't know" or "DK" options in potentially ambiguous surveys.
Including demographic questions at the end of questionnaires.

Creating an Effective Survey (Page 7)

Importance of clear wording in survey questions to avoid ambiguity.
Using pilot studies to identify potential issues in survey wording / design.
Avoiding leading or biased questions.
Importance of avoiding double-barreled questions.

Collecting Survey Data (Pages 8-9)

In-person interviews, including benefits (e.g., follow-up possibilities) and drawbacks (e.g., costs, interviewer bias).
Strengths and weaknesses of mailed or paper surveys (e.g., ease of scoring and costs).
Advantages and disadvantages of phone surveys (e.g., efficiency, required brevity, and response rate, as well as the problem of call avoidance).
Benefits and limitations of electronic surveys, including issues like sampling, ethics, and efficiency

Analyzing Data from Non-Experimental Designs - Correlation (Pages 10-12)

Correlation describes relationships between variables without establishing a causal link.
Defining positive, negative, and no correlation.
Creating scatterplots (see Figure 9.1) to visualize correlations.
Example of positive correlation relating study hours and GPA, and an example of negative correlation relating goof-off hours and GPA to demonstrate differing relationship types.

Analyzing Data from Non-Experimental Designs - Scatterplots (Page 13-14)

Scatterplots visually represent relationships between two variables.
Interpreting scatterplots to determine the strength and direction of a correlation (see Figure 9.1 & 9.2).

Analyzing Data from Non-Experimental Designs - Positive / Negative Correlation (Pages 11, 12)

Examples of scatterplots representing positive and negative correlations.
Identifying the nature of the correlation using visual data inspection (e.g., positive/negative, weak/moderate/strong).

Analyzing Data from Non-Experimental Designs - Correlation Coefficients (Page 16)

Pearson's r, Spearman's rho, and phi coefficient—types of correlation coefficients.
Interpreting correlation coefficients: magnitude (strength) and direction (positive/negative).

Analyzing Data from Non-Experimental Designs - Coefficient of Determination (Page 17)

Calculating and Interpreting r² (coefficient of determination).
Understanding the proportion of variance in one variable explained by another.
Recognizing unexplained variance.

Analyzing Data from Non-Experimental Designs - Outliers (Page 19)

Recognizing outliers in data sets.
Potential impact of outliers on correlation coefficients (r and r²).
How outliers can impact interpretations.

Analyzing Data from Non-Experimental Designs - Regression (Pages 20-21)

Predicting outcomes using regression analysis, including its value in estimating and testing accuracy.
Understanding regression line—a straight line that best summarizes the correlation in data. General regression equation (Y = a + bX).
Identifying the criterion variable and predictor variable in regression analysis.
Interpret and apply formulas that show the relationship between criterion (Y) and predictor (X) variables.
Providing examples of regression analysis, such as predicting GPA from study hours and goof-off hours.

Analyzing Data from Non-Experimental Designs - Regression: Linear and Multiple (Page 22)

Using linear regression to make predictions using one predictor variable
Using multiple regression to make predictions using multiple predictor variables

Analyzing Data from Non-Experimental Designs - Interpreting Correlational Results (Pages 23, 24)

Recognizing the directionality problem in correlational studies.
Using cross-lagged panel correlations to understand the direction of causality between variables. (See Figure 9.5).
Distinguishing mediating (how/why) from moderating (under what conditions) variables in interpreting correlations (see Figure 9.6).

Summary (Page 25)

Purpose of surveys in psychology.
Importance of clear research questions.
Significance of correlation and regression for data analysis in non-experimental designs, including surveys.
Importance of acknowledging directionality and third variables in non-experimental studies.
Role of non-experimental research in exploratory studies and preliminary data collection.

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Dive into Chapter 9 of your psychology coursework, focusing on non-experimental design and survey methods. Learn about the crucial principles of survey design, the different methods of data collection, and the interpretation of survey results. This quiz will help reinforce your understanding of sampling issues, correlation, and regression analysis in psychological research.