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Part 1: SPSS: Recode Likelihood To Recommend

Follow this procedure to transform the ratings of likelihood to recommend from the Avery Fitness Center Data Set to transform this variable from a 10-point rating scale to a dichotomous variable with 2 levels loyal and not loyal.  Use the video at the bottom of the page as an additional reference.

1. Select TRANSFORM.

2. Click on RECODE and select INTO DIFFERENT VARIABLES…

3. Click on recom and move it to NUMERIC VARIABLE OUTPUT VARIABLE box.

4. Type “rrecom” in OUTPUT VARIABLE NAME box.

5. Type “loyalty” in OUTPUT VARIABLE LABEL box.

6. Click OLD AND NEW VAULES box.

7. Under OLD VALUES on the left, click RANGE. Type 0 and 6 in the range boxes.  Under NEW VALUES on the right, click VALUE and type 1 in the value box. Click ADD.

8. Under OLD VALUES on the left, click RANGE. Type 7 and 10 in the range boxes.  Under NEW VALUES on the right, click VALUE and type 2 in the value box. Click ADD.

9. Click CONTINUE.

10. Click CHANGE.

11. Click OK.

Depending on the SPSS version, you must then go to the data view to create value labels for the recoded variable.

For the new variable rrecom code 1 can be labeled “not loyal” and code  2 can be labeled “loyal” as your recoding put lower ratings 0-6 in code 1 and higher ratings 7-10 in code 2.  To understand how to edit your data file to create a data labels for this newly created variable see this video.  The likelihood to recommend variable in research is a variable to understand customer loyalty.

Creating Data Labels with SPSS:  https://www.youtube.com/watch?v=sSoOY99XqZ4

Video Recoding Variables with SPSS:  https://www.youtube.com/watch?app=desktop&v=4xXpyi7Dya0

Recode the Likelihood To Recommend variable in the Avery Fitness Data Set.  Create a pie chart of the distribution of the recoded variable showing the percent loyal and not loyal.  Use the snipping tool or print screen to show the image on a Word Document.  Recode one other quantitative variable in the  data set of your choice to a dichotomous variable (two categories).  Create a pie charts showing the distribution of the newly recoded variable.

Part 2: Descriptive Statistics with Excel

Please watch the video below to learn how to calculate Descriptive Statistics using Excel. The video is posted below as well. The spreadsheet with data is on the course site. Using the video as a guide, add the formulas and calculate the descriptive statistics using EXCEL.  Recreate the spreadsheet as described in the video and show a print screen or use the snipping tool to show your work.

VIDEO: Descriptive Statistics with Excel:  http://link.brightcove.com/services/player/bcpid790261335001?bckey=AQ~~,AAAAPmbRRLk~,C5G7jhYNtifB7aWTdZf87KOT82XYugjP&bctid=2277365305001

Part 3:  Hypothesis Testing, Cross tabulations and the Chi Square Test  

Research Question: Is there a difference is usage of any other services (see the next slide for guidance) at the Avery Fitness Center based on doctor’s recommendation?

State the null hypothesis Ho and the alternative hypothesis Ha.

Is there any area where the null hypothesis can be rejected?

Null Hypothesis: e.g. no effect, no difference between groups.  Hope to reject the null: Ho

Alternative Hypothesis: e.g. there is a difference between groups.  Hope to accept the alternative: HA

Create the appropriate crosstabulations and then calculate the Chi Square Test and Phi and Cramer’s V.  Interpret the result.  See the next slide for the variables to use.

Research Question: Is there a difference is usage of any other services at the Avery Fitness Center based on doctor’s recommendation?

State the null hypothesis Ho and the alternative hypothesis Ha.

Is there any area where the null hypothesis can be rejected?

Null Hypothesis: e.g. no effect, no difference between groups.  Hope to reject the null: Ho

Alternative Hypothesis: e.g. there is a difference between groups.  Hope to accept the alternative: HA

 
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