2 scenerios which means there will be 2 word explanations and 2 output files and 2 analysis. please have 3 files attached per analysis separate the two scenerios files

In Chapter 1 you read about the differences between experimental and observational research and read that correlational studies are one type of observational research. In an experiment, the researcher manipulates a variable to determine differences between two or more levels of that variable. In an observational study, the researcher looks at patterns of relationships without manipulating variables. In correlational studies, you cannot show that one variable *causes* a change in another variable. However, you can demonstrate that as one variable increases, another increases. You also may find that as one variable increases, the other decreases. You may even find that there is no relationship at all. Use your understanding of correlations to work through the following scenario.

**Scenario:**

To prepare for this Assignment, recall that in Week 1 you imagined you were a researcher interested in determining if student intelligence is related to self-esteem. Now imagine that 10 individuals participated in your study and the raw data are given here:

Participant Self-Esteem Score IQ 1 3.2 100 2 4.1 140 3 2.2 95 4 3.0 112 5 2.6 130 6 2.0 99 7 5.0 118 8 4.8 121 9 3.7 129 10 4.4 138

**Assignment:**

**To complete this Assignment, submit by Day 7** your answers to the following. Based on the scenario, use SPSS to determine if self-esteem is related to intelligence in your sample by computing a correlation. Save and submit both the SPSS data and output files.

- Before computing the correlation, state either a one-tailed or two-tailed, alternative hypothesis and the corresponding null hypothesis in words (not formulas).
- Based on the hypotheses you stated, explain whether you should conduct a one-tailed or two-tailed test. Provide a rationale for your choice.
- Identify what the correlation coefficient (
*r*) is for this data set. - State the degrees of freedom and explain how it is calculated.
- Identify the
*p*value. - Explain whether you should retain or reject the null hypothesis. Provide a rationale for your decision.
- Describe the direction and strength of the relationship between self-esteem and intelligence.
- Submit three documents for grading: your text (Word) document with your answers and explanations to the application questions, your SPSS Data file, and your SPSS Output file.

Previously in this course, you worked with parametric statistics like* t *tests, ANOVAs, and correlations. In order to use parametric procedures, your dependent variables must be measured on either an interval or a ratio scale. For this Assignment you will examine the nonparametric procedure called chi-square, which allows you to analyze nominal data compared to parametric tests that allow you to analyze interval and ratio data. Consider this example: You are curious whether males report that they like statistics more frequently than females report that they like statistics. You decide you will ask them a yes-or-no question, and that involves nominal data. You would then count the numbers of responses of yes and no for males and for females.

Nonparametric procedures allow you to compare the male responses to the female responses and determine if gender and enjoyment of statistics are independent from each other (not related). Understanding chi-square will help you to more fully understand research studies that utilize nominal variables.

**Scenario:**

To prepare for this Assignment, imagine that you have information about 30 other participants’ self-esteem and intelligence, but for these individuals you only have data on whether they have average or above average intelligence, and whether they have high or low self-esteem. You do not have their actual scores for each variable. The observed frequencies are reported here:

Intelligence Average Above AverageSelf-Esteem Low 7 8High 5 10

**Assignment:**

**To complete this Assignment, submit by Day 7** your answers to the following. Based on the scenario, use SPSS to determine if intelligence is related to self-esteem in your sample by computing the appropriate chi-square test. Save and submit both the SPSS data and output files.

- Explain what scale of measurement is used to measure intelligence in this example. How do you know?
- Explain what scale of measurement is used to measure self-esteem. How do you know?
- Before computing the chi-square, state your null and alternative hypotheses in words (not formulas).
- State whether this scenario requires a one-way or two-way chi-square test. Explain your answer.
- Identify the obtained χ2.
- Identify the degrees of freedom and explain how it is calculated.
- Identify the
*p*value. - Explain whether you should retain or reject the null hypothesis and why.
- Explain what you can determine about the relationship between self-esteem and intelligence, based on this set of data.
- Submit three documents for grading: your text (Word) document with your answers and explanations to the application questions, your SPSS Data file, and your SPSS Output file.

This page contains the Learning Resources for this week. Be sure to scroll down the page to see all of this week's assigned Learning Resources.

- Heiman, G. (2015).
*Behavioral sciences STAT 2*(2nd ed). Stamford, CT: Cengage.- Chapter 10, “Describing Relationships Using Correlation and Regression” (pp.162-181)
- Chapter 13, “Chi Square and Nonparametric Procedures” (pp.218-229 only)
- Chapter 10 Review Card (p. 10.4)
- Chapter 13 Review Card (p. 13.4)

- Bjorkman, S. (2014).
*SPSS tutorial - Chi-square*. Retrieved from http://screencast.com/t/mJsqW8p7

Note: The approximate length of this media piece is 5 minutes. This video demonstrates calculating and interpreting chi-square analyses in SPSS. - Ludwig, T. E. (n.d.a).
*Correlation*[Interactive media]. Retrieved June 11, 2013, fromhttp://bcs.worthpublishers.com/WebPub/Psychology/psychsim5/PsychSim5%20Tutorials/Correlation/Correlation.htm

Note: This site offers additional information about correlations, including interactive media examples. - Son, J. (2011
*). Statistics – Regression*[Video file]. Retrieved fromhttp://www.youtube.com/user/EducatorVids2?v=51JcydfYaTY&feature=pyv**Note:**The approximate length of this media piece is 5 minutes.

This video explains linear regression, including predictor and response variables. - StatsLectures. (2011d).
*SPSS - Pearson's r (+hypothesis test)*[Video file]. Retrieved fromhttp://www.youtube.com/watch?v=jexXeAoymh4**Note:**The approximate length of this media piece is 4 minutes.

This video shows how to calculate Pearson’s*r*in SPSS. In addition, a hypothesis test is conducted to determine if the Pearson’s*r*is significant.

- BBC (Producer). (2010).
*The joy of stats*[Video series]. Retrieved fromhttp://www.bbc.co.uk/programmes/p00cgkfk- “Hans Rosling’s 200 Countries, 200 Years, 4 Minutes”

- University of South Carolina. (n.d.a).
*Regression applet.*Retrieved June 11, 2013, fromhttp://www.stat.sc.edu/~west/javahtml/Regression.html - University of South Carolina. (n.d.b).
*Understanding correlation.*Retrieved June 11, 2013, fromhttp://www.stat.tamu.edu/~west/applets/rplot.html

Subject | General |

Due By (Pacific Time) | 11/20/2015 12:00 am |

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