Good afternoon Spencer. I have two homework assignments for you. I will post one here, and then a separate one after this.  

 

First thing my professor responded to the homework you just did, and stated great job, but now she has the following question for you, I need answered:

 

If the researchers asked you to analyze the data they had already collected (that is, you couldn’t change anything about how they conducted the study), what statistics would you recommend they run and why?

 

Second thing is could you respond to the following scenario from a classmate, and answer professors methods at the end of the scenario. Thanks. Here is my classmates scenario:

 

 

In this scenario, the factor is different brand of basketball shoes. The alpha shoe company used 5 levels in total to compare the mean of jumping height in comparison to their brand “Pluto”. They showed that the mean jumping height of their company is the highest by comparing the means from other 4 brands. After reading the advertisement, I was wondering that why they used such a small sample. I also wanted to know if they used random participants or those players who has higher jumping ability.  

 

The company used the mean to draw a conclusion. I believe mean is a good descriptive measure of data because it includes all the observation and scores into account, it is usable in further analyses, and it is the most stable of the measures of central tendency. Therefore, I would use mean to draw a conclusion. However, mean has its own limitation in such that the

 

 According to Wolkowitz et al., (2012), the greater the number of the sample mean, the more likely we are to make to make at least one type 1 error. To overcome this, we can use a procedure to test 5 different means for statistical significant simultaneously. The procedure is called analysis of variance abbreviated as ANOVA.  If the result of ANOVA was significant, then we must perform the post hoc tests so that we can find out which group is different than another or whether “Pluto” is significantly different from x brands of shoes.  It is also better to use a sample sizes that are approximately equal with equal population variances. It is also best to use F ratio. According to Wolkowitz et al., (2012), total variance is divided into between- group variance and within-group variance which can be compared by F ratio. F ratio determine whether the independent variable (different brands of basketball shoes) has effect on the dependent variable (jumping height).

 

Here is what you are suppose to answer per professor methods.

 

Support or challenge key points of the explanations provided 

Support or challenge key points of a follow-up study recommendation and provide additional information to consider.

 

 

Thanks Spencer

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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