SPSS assignment, 3 parts of questions

Due: Nov. 1

To Be Completed Individually

The purpose of this assignment is to learn how to analyse data using SPSS. Please read the assignment carefully to ensure that you have done what was asked and have answered all questions. Do not forget to save your data file, output files and provide printouts of your data file and all of your analyses. You should also indicate which analysis goes with which question. When asked for hand calculations, please SHOW ALL OF YOUR WORK to avoid losing points.

Part I.

Enter the following data into an SPSS spreadsheet (in the data view window)

Calculate the following:

1) Frequency of males and females

2) Mean and standard deviation for Self-esteem score.

3) Mean and standard deviation of Achievement motivation score

4) Minimum, Maximum and Range for Age

5) Plot a histogram for Self-esteem score with the normal curve

6) Plot the histogram for Achievement motivation score with the normal curve

7) Use a scatterplot to represent the relationship between Self-esteem score and Achievement motivation score. Place Self-esteem score on the X axis and Achievement motivation score on the Y axis.

8) Calculate the Pearson product moment correlation for Self-esteem score and Achievement motivation score by hand. You can assume that the variables are ratio and interval in nature, respectively. Make sure that you show your work.

9) Perform a Pearson product moment correlation on Self-esteem score and Achievement motivation score using SPSS. Make sure you take all the proper steps when performing the correlation. Report this value.

10) Comment on the strength and direction of the correlation between Self-esteem score and Achievement motivation score.

11) Is a Pearson analysis appropriate given the data? Provide three reasons or pieces of evidence to support your conclusion (you can’t give interval data as one of your reasons because you already know that).

12) Convert the raw scores to z scores for each variable (using SPSS) and re-run the Pearson analysis in SPSS. What do you notice?

Part II.

Your lab mate was interested in the link between anxiety and students’ academic self-efficacy. She recruited 25 Psychology majors to complete the 19-item College Self Efficacy Instrument (CSEI; Solberg et al., 1993) and the 10-item Anxiety scale of the Depression, Anxiety and Stress Scale (DASS; Lovibond & Lovibond, 1995). She ran a Pearson correlation because both measures were interval in nature. There were also no outliers or skew. She predicted that there would be a significant relationship between the two variables, but she was surprised when she found non-significant results, r(23) = -.120, p >.05. She concluded that there was no relationship between anxiety and students’ academic self-efficacy, but she wanted you to look at the data in case she did something wrong. She sent you the data file and the value of the statistic she obtained, but not the output so you could start your analyses from scratch. However, without the output, you don’t know how she plotted his data. You ask her and she says that she put anxiety score on the X axis and academic self-efficacy score on the Y axis. The data file she sent is called spssdata18.sav (you can find this data file on ACORN).

1) Was her choice of statistic appropriate? Explain your reasoning.

2) Do you agree with her that there is essentially no relationship between anxiety score and academic self-efficacy score? Explain your reasoning.

Part III.

You conduct a study to examine the relationship between outlook on life and life satisfaction. People rated their outlook on life as: very negative, somewhat negative, neither negative nor positive, somewhat positive, or very positive. Participants were then asked to rate their life satisfaction as: very unsatisfied, somewhat unsatisfied, neither unsatisfied nor satisfied, somewhat satisfied, or very satisfied. What type of correlational technique should you use for the data that you will obtain from this study? Explain your reasoning.