You just finished teaching your first PSYCH 248 lab section, and it’s time to calculate the grades. Your wonderful teaching assistant created an Excel file with all of the students’ exam grades, homework grade, and lab grade as well as their gender. Your next steps are to calculate each student’s final grade, convert those scores to letter grades, and describe the distribution of scores.

MATLAB: An Introduction with Applications
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Chapter1: Starting With Matlab
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Background: You just finished teaching your first PSYCH 248 lab section, and it’s time to calculate the grades. Your wonderful teaching assistant created an Excel file with all of the students’ exam grades, homework grade, and lab grade as well as their gender. Your next steps are to calculate each student’s final grade, convert those scores to letter grades, and describe the distribution of scores.
 
 

2. In Excel, calculate the final Number Grade, Letter Grade, and Z-score for each student.
a. To calculate the Number Grade, type a numerical equation after an = sign in a cell or use the =AVERAGE() formula; however, keep in mind that the =AVERAGE() formula will always give you the regular mean, not the weighted mean. Grades for this course are comprised of three parts: lecture exams (60%), homework (20%), and lab (20%).
 
b. To calculate the Letter Grade, use the =IF() formulawith a series of logic statements or enter the data by hand. For this assignment, let’s convert Number Grade into Letter Grade using the following rubric: A (90-100), B (80-89), C (70-79), D (60-69), F (<60).
 
c. To calculate the Z-score, use the =STANDARDIZE() formula on the Number Grade variable. This formularequires three components: x (i.e., one student’sNumber Grade), the sample mean, and the sample standard deviation. You can calculate the sample mean and standard deviation for Number Grade using the =AVERAGE() and =STDEV() formulas.
 
i. Create a new column called Abs(Z-score). In this column, use the =ABS() formula on the Z-score variable you just created to get the absolute values of each Z-score.
 
3. Now that you have filled in your dataset, save your file and open it in JASP.
a. In the Data View, apply value labels to the Gender variable by clicking on the title of the column and entering the labels accordingly (0=Woman, 1=Man).
b. Make sure that each variable has the correct “column type” (i.e., nominal, ordinal, or scalar).

1. Row vs. Column
a. Are the data entered in row format or column format?
b. What is one advantage of entering data in row format?
 
2. For the variables below, state whether they are independent, quasi-independent, or dependent variables in this situation. Briefly explain why.
a. Gender
b. Number Grade
 
3. For the following variables, state whether they are nominal, ordinal, interval, or ratio:
a. Gender
b. Number Grade
c. Letter Grade
d. Z-score
 
4. Weighted Mean
a. Did you have to calculate the Number Grade variable using the weighted mean? Why?
b. When should you use the weighted mean instead of the regular mean?
 
 
**I have no idea where to start*
The table presents student performance data across various evaluation components. Each row corresponds to a student, identified by their ID number.

**Columns:**

1. **ID Number**: Unique identifier for each student.
2. **Gender**: Coded as 0 for Woman and 1 for Man.
3. **Exam 1**: Score obtained in the first exam.
4. **Exam 2**: Score obtained in the second exam.
5. **Exam 3**: Score obtained in the third exam.
6. **Homework**: Score representing the student's homework performance.
7. **Lab**: Score reflecting the student's lab performance.
8. **Number Grade**: The overall numerical grade, calculated from the separate components.
9. **Letter Grade**: The corresponding letter grade based on the number grade.
10. **Z-Score**: A statistical measurement that describes a value's relation to the mean of a group of values.

This dataset can be used for statistical analysis on performance trends, gender comparisons, or the correlation between different assessment types and overall grades.
Transcribed Image Text:The table presents student performance data across various evaluation components. Each row corresponds to a student, identified by their ID number. **Columns:** 1. **ID Number**: Unique identifier for each student. 2. **Gender**: Coded as 0 for Woman and 1 for Man. 3. **Exam 1**: Score obtained in the first exam. 4. **Exam 2**: Score obtained in the second exam. 5. **Exam 3**: Score obtained in the third exam. 6. **Homework**: Score representing the student's homework performance. 7. **Lab**: Score reflecting the student's lab performance. 8. **Number Grade**: The overall numerical grade, calculated from the separate components. 9. **Letter Grade**: The corresponding letter grade based on the number grade. 10. **Z-Score**: A statistical measurement that describes a value's relation to the mean of a group of values. This dataset can be used for statistical analysis on performance trends, gender comparisons, or the correlation between different assessment types and overall grades.
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