Order instructions
This lab can be performed by one student or two in the lab or on another computer that uses Microsoft Excel as long as the student has access to the data sets required. This lab assumes a familiarity with the basic functions of the Excel application and that the student will practice the statistical functions needed to work the lab.
In the last lab, we organized the data into a useful form that could be used to test hypotheses about two independent samples to determine if they were significantly similar or not. What if we want to determine simply if two variables are related at all? This calls for correlational statistical methods. In particular, in this lab, you will learn how to apply the Pearson correlation to samples of data from the original Lab 1 dataset which has been updated to included data on student grade point average (GPA). You will organize the data into arrays that can be operated on by Excel functions. You will select the functions that allow you to determine a Pearson correlation coefficient, derive the appropriate statistic, and make a decision whether to reject the null hypothesis. From this you will interpret your results.
For this lab you will need the following items:
Computer running Windows XP operating system (Mac running OS 10.6 or earlier)
Microsoft Excel 2003 or later version
Data set: Lab_3_Correlation_Data.xls (download from portal)
Goals of the lab:
1. To become more competent in the use of the statistical functions of Microsoft Excel.
2. To make concrete use of the concepts of correlation and covariability in the context of inferential statistics for real data sets.
3. To determine and to display the data and results in a manner visually appropriate to the Pearson r and r2 statistics.
Assignment
1. Create a folder on the desktop of your PC titled:
“Stat 101_[Your FirstNameLastName]_Lab3”
2. Download to that folder the data set “Lab_3_Correlation.xls” from the portal.
3. Open that data set in a new Excel window.
4. Think ahead. When you are done today, be sure to email yourself a copy of your worked dataset so that you have a backup to work on at home.
5. Recall from previous labs that the data set you have opened contains three variables: SCHOOL (the school the students attended when they took the Psychology 1 class), GRADE (the letter grade the student earned in the class), and FINAL (the score the student got on the final exam).
6. To this has been added another column of data: GPA, the grade point average of each student at the time that he or she took the final exam for that Psychology 1 class.
This data is not yet in a form that would allow you to test hypotheses about relationships among the possible variables from the different SCHOOL populations. Also, the size of the data set is still a bit difficult to handle. We need to sample from the larger population to produce two groups of equal sample size so we can test hypotheses of covariance about them.
7. Dr. Farris has used the RANDBETWEEN function in Excel to randomly select two samples of equal size, one from each of the LAVC and Monroe High School populations. These are not the same subjects that were selected for Lab 2.
8. Using this information, you will consider what hypotheses the data will allow you to test. Consider all that you know, and do not know, about these samples in making your decisions.
9. Follow the four steps of hypothesis decision-making for the Pearson r. Show all your calculation work, or state the reasons for your decisions, at the end of each step.
10. You may refer to your text and notes for guidance. For your chosen research question, you will print a report that includes:
(1) the scale of measurement;
(2) provide the appropriate null hypotheses, correctly stated;
(4) provide the appropriate alternate hypotheses, correctly stated;
(5) provide the output from Excel (attach to your report) the appropriate table including all main calculations from the equations at each step of the Pearson r method. You do not need to print all the data from the dataset, just those columns and rows that you used in your analysis;
NOTE: organize your tables and charts in your Excel worksheet(s) so that when they are printed all items fall neatly within a page either in portrait or landscape page orientation;
(6) provide the chart (graph) of the results (this will be different from past graphs);
(7) print the output of Excel and graph. You may combine these into one Word document, if you wish;
(8) type a paragraph which explicitly describes the steps you took to organize your data and to test your hypotheses; and
(9) type no more that a one paragraph summary of what the output shows. Write this so clearly that an intelligent high school senior could understand it. For instance, you might have another college student who has not taken statistics read it and comment on its clarity.
