Reflection – Discussion Reflection and Pulling It All Together This class has covered a lot of impor

Reflection – Discussion

Reflection and Pulling It All Together

This class has covered a lot of important statistical techniques, research methods, and how to use and interpret SPSS. This course was designed to emphasize several goals: 
 

1) Analyze the relationship between two or more variables using the appropriate statistical technique. 

2) Compare group means with a single or multiple independent variables using the appropriate statistical test. 

3) Interpret correctly the output from SPSS analyses/statistical tests. 

a. Imagine and Describe Your Dream Job: Describe, using at least one paragraph, a perfect job in your area of interest. 

b. Research in Your Area: Imagine that you are in charge of a research Assignment, and can choose to do research on anything. What research question would you create? Write out your research question and explain any terms or ideas. Develop a research hypothesis that you might use to answer your question. 
…….
…..
c. Using SPSS: During this course, you used SPSS to look at summary statistics, like mean or variance, to make graphs, to calculate correlation and regression, and to run hypothesis tests, such as t-tests and ANOVA tests. Which SPSS method(s) do you think you will use to answer your research question? Why? 

d. Tell Us What You Think: Are you planning to add SPSS to your resume/CV? Do you plan to use SPSS again in the future? What did you like best about this class? What would you change about this class to create a better learning experience for future students? 

Looking back: A Fun Review Let us look back: Units 1 and 2 covered descriptive statistics such as graphs and charts and numerical measures such as mean and variance. Units 3 and 4 covered correlation, regression, and prediction. Scatterplots were used to illustrate relationships between variables and regression was used to create prediction equations for highly correlated variables. Units 5, 6, and 7 introduced inferential statistics and hypothesis testing. In Unit 7, you considered the t-test for independent means, and you used this test to compare two sample groups from an independent variable In Unit 7, the research example was whether creating video lectures for students will significantly affect total class points. The sample was a class of 30 students. To research this question, I gave 15 students access to video tutorials each week, and the other 15 did not have access. The dependent variable was 
total class points. My question was whether the mean total class points for Group1 (students WITH video access) was significantly different from Group 2 (students WITHOUT video access). Ho: mean total points Group1 = mean total points Group2 Ha: mean total points Group1 ≠ mean total points Group2 Then, in Unit 8, you expanded this concept into having an independent variable that is separated into
more than two groups.  
…….
….. Instead of comparing only two means (Group 1 and Group 2), you compared three different groups (all within our single independent variable of “video access”): Group 1: Watches all videos (1 per week) Group 2: Watches half of the videos (1 every other week) Group 3: Watches none of the videos (no access to videos) Again, my single independent variable was
 video access. In Unit 8, it was separated into three groups (sometimes as called levels or classes) Because you wanted to compare the mean total points for all three groups, you used a one-way -ANOVA test (rather than a t-test which is used for 2 groups). Ho: mean total points Group1 = mean total points Group2 = mean total points Group3 Ha: mean total points Group1 ≠ mean total points Group2 ≠ mean total points Group3 In Unit 9, we expanded this concept once again, and added a second independent variable.
Independent Variable 1: Video Access Group 1: Watches all videos (1 per week) Group 2: Watches half of the videos (1 every other week) Group 3: Watches none of the videos (no access to videos)
Independent Variable 2: Gender Group 1: Male Group 2: Female
Dependent Variable: Total Class Points A two-way ANOVA (Factorial ANOVA) was used to determine if there are any significant differences or interactions between the means of our groups. There are three null hypotheses and three alternative hypotheses.
Ho1: There is no difference in the mean total class points between the three video access groups.
Ho2: There is not difference in the mean total class points between males and females.
Ho3: There is no Interaction between the two independent variables.
Ha1: There is a difference in the mean total class points between the three video access groups.
Ha2: There is a difference in the mean total class points between males and females.
Ha3: There is an Interaction between the two independent variables. Now it’s your turn to apply all that you have learned to your perfect job and your area of interest!
e. Submit: Paste your completed Word document to this area. If your SPSS item(s) do not paste properly, also attach your full Word document to your post, and note in your post that the SPSS items are attached. Remember that your goal for the Discussion is to ensure: 

  • Responses are on topic, original, and contribute to the quality of the Discussion
  • Responses make frequent, informed references to unit material
  • Responses are clearly written
  • A minimum of two or more responses per thread to classmates that are thoughtful and advance the Discussion are required

Please try to make your initial posts no later than Sunday night to give your classmates an opportunity to respond. Be sure your post is grammatically correct, has been spell checked, and fully answers the question. Be sure to comment on and respond to your classmates’ postings throughout the week.
…….
…..

Get your college paper done by experts

Do my question How much will it cost?

Place an order in 3 easy steps. Takes less than 5 mins.