# unit 2 discussion

**Question description**

Unit 2 Descriptive Statistics

Applied Statistics for Psychology

Instructions: For this project assignment, you will use the “Statistics Class” dataset called Stat_Grades.sav, which can be found in the Doc Sharing area under the Graded Projects category. This same “Statistics Class” dataset will also be used for the projects in Units 4, 7, and 9. There is a full description of this dataset in the Graded Projects category of the Doc Sharing area. The Stat_Grades.sav dataset contains data collected about statistics students in three sections of a statistics class taught by an instructor. You will also use SPSS for this project, and will have to have SPSS already installed and running on your computer.

HINTS AND HELP

Note: When asked to explain or discuss, make sure you use complete sentences, paragraph form (single spacing), proper grammar, and correct spelling. Minimal or incomplete responses can lose points. Include any SPSS results that you use, but do not include SPSS results that are not part of your solution.

Hint: In some cases, you are asked to determine which graphical and numerical descriptors are “appropriate” to describe each variable. This means that you will have to determine which graphs you feel are best and why. You will also need to determine which numerical descriptors best describe each variable and why.

Remember that numerical descriptors include things like mean, median, mode, variance, standard deviation, range, min, max, etc… Some are appropriate in some cases and some are not. This is for you to determine as an important part of the project.

Remember to use the Live Binder for further assistance

You may type and place your answers and SPSS results directly into this document.

For Extra Help and Instructional Videos, please see the Live Binder for this Unit.

Assignment Rubric Reminder for Unit 2 at the “A” range. Please check the class syllabus for a full rubric.

MM570 Unit 2 Project Grading Rubric

Possible Points: 100

Point Possible

Grading Criteria

90 - 100 points

Student work demonstrates mastery of the objectives assessed by the project. This is evidenced by at least the following:

· Appropriate data were selected to describe the students in the class.

· Appropriate graphs were used to describe the data selected.

· The selection of the statistical procedure is appropriate for describing the data selected.

· The appropriate descriptive statistics were calculated correctly using SPSS.

· The interpretation of the SPSS output is correct and complete.

· Inappropriate or unrelated SPSS outputs are not included.

Unit 2 Research Questions

1. There are many variables in the Student Data set (Stat_Grades.sav) that can be used to describe the students in the class. Consider the variable “Ethnicity” and answer the following questions:

a. Using the Variable View in SPSS, write out how each ethnicity is labeled and note how many ethnic groups are included.

b. What type of data does the “Ethnicity” variable represent? Is the data discrete or continuous? How can you tell? Is the data qualitative or quantitative? How can you tell? Is the data nominal, ordinal, ratio, or interval? How can you tell?

c. Which descriptive numerical measure best describes the variable Ethnicity? Use SPSS to output ONLY that one numerical measure. Include it here. Why is that numerical measure the most appropriate? What information does that measure tell you about the students in the Statistics Class (Stat_Grades.sav)?

d. Which descriptive numerical measure is LEAST appropriate to describe the variable Ethnicity? Use SPSS to output ONLY that one numerical measure. Include it here. Why is that numerical measure the least appropriate? What information does that measure tell you about the students in the Statistics Class (Stat_Grades.sav)?

e. Choose the most appropriate graph to represent the variable ethnicity. Create the graph in SPSS and include it here. Be sure the graph is fully labeled. Discuss why you chose this graph type and what it tells you about the students in the class.

2. There are many variables in the Student Data set (Stat_Grades.sav) that can be used to describe the students in the class. Consider the variable “Previous GPA” and answer the following questions:

a. What type of data does the “Previous GPA” variable represent? Is the data discrete or continuous? How can you tell? Is the data qualitative or quantitative? How can you tell? Is the data nominal, ordinal, ratio, or interval? How can you tell?

b. Which descriptive numerical measure best describes the variable Previous GPA? Use SPSS to output ONLY that one numerical measure. Include it here. Why is that numerical measure the most appropriate? What information does that measure tell you about the students in the Statistics Class (Stat_Grades.sav)?

c. Which descriptive numerical measure is LEAST appropriate to describe the variable Previous GPA? Use SPSS to output ONLY that one numerical measure. Include it here. Why is that numerical measure the least appropriate? What information does that measure tell you about the students in the Statistics Class (Stat_Grades.sav)?

d. Choose the most appropriate graph to represent the variable Previous GPA. Create the graph in SPSS and include it here. Be sure the graph is fully labeled. Discuss why you chose this graph type and what it tells you about the students in the class. Why is a Pie Graph an inappropriate option? Create a Pie Graph in SPSS and include it here. Compare both graphs and discuss why one graph is more appropriate than the other.

3. Choose any two other appropriate variables in the class (Stat_Grades.sav) and use both to evaluate, describe, and discuss how the students are performing in the statistics class. Include both numerical measures and graphs in your conclusions and discussion. Note: student performance relates to how students are doing on assessments and/or how they are doing overall. Think about which variables tell you how students are doing in the class.

## Tutor Answer

## Review from our student for this Answer

Brown University

1271 Tutors

California Institute of Technology

2131 Tutors

Carnegie Mellon University

982 Tutors

Columbia University

1256 Tutors

Dartmouth University

2113 Tutors

Emory University

2279 Tutors

Harvard University

599 Tutors

Massachusetts Institute of Technology

2319 Tutors

New York University

1645 Tutors

Notre Dam University

1911 Tutors

Oklahoma University

2122 Tutors

Pennsylvania State University

932 Tutors

Princeton University

1211 Tutors

Stanford University

983 Tutors

University of California

1282 Tutors

Oxford University

123 Tutors

Yale University

2325 Tutors