solved Draft a reply to another student’s discussion board post. Here

Draft a reply to another student’s discussion board post. Here are the instructions: The student must then post 1 reply to another student’s post. The reply must summarize the student’s findings and indicate areas of agreement, disagreement, and improvement. It must be supported with scholarly citations in the latest APA format and corresponding list of references. Here is the students post you are responding to: D3.4.1 Using Outputs 4.1a and 4.1b: (a) What is the mean visualization test score? (b) What is the skewness statistic for math achievement tests? What does this tell us? (c) What is the minimum score for mosaic pattern test? How can that be? The mean of the visualization test score is 5.2433. The Skewness statistic for the math achievement test is .044. This tells us the data for math achievement is not significantly different from normal, with a slight positive skew from a normal distribution (Mason, 2013). -4.0 is the minimum score for the mosaic pattern test. This was the bare minimum possible score which means that at least one answer for all the students had to score the minimum. This could also be an error that needs to be investigated to ensure that the data is correct. It would be challenging to believe that this score result is accurate (Mason, 2013). D3.4.2.Using Output 4.1b: (a) For which variables that we called scale, is the skewness statistic more than 1.00 or less than –1.00? (b) Why is the answer important? (c) Does this agree with the boxplot for Output 4.2? Explain. The data from 4.1b shows that the skewness for all but one variable was between -1.00 and 1.00. The one statistic was the competence scale and had a result of -1.634 (Mason, 2013). This answer is important because further investigation is needed to discover what caused the competence score skewness outside the normal range. This can be caused by multiple outliers that generated the data to pull the skewness to one side significantly (Mason, 2013). The boxplot explains the previous answer in output 4.2. The box plot shows data from the competence score having four significant outliers well below the rest of the participants. The low scores from the outliers caused the skewness statistic to be below -1.00 (Mason, 2013). D3.4.3.Using Output 4.2b: (a) How many participants have missing data? (b) What percent of students have a valid (non-missing) motivation scale or competence scale score? (c) Can you tell from Outputs 4.1 and 4.2b how many are missing both motivation scale and competence scale scores? Explain. Based on the output from 4.2b, there are 4 participants missing data. The percent of students with valid data for motivation scale and competence scale is 94.7% (Mason, 2013). The outputs from 4.1 do show data missing; however, for motivation score and competence score, it shows 73 for each variable, meaning there are two missings. The N value in 4.1 does show 71 valid. The output from 4.2b shows this is not the case, and the number is 71 with four missings, which lines up with the N value from 4.1 output. This would need to be researched to ensure that all data was entered correctly as the data for these two variables from the missing information could be found. The data would be excluded from the outputs (Mason, 2013). D3.4.4.Using Output 4.4: (a) Can you interpret the means? Explain. (b) How many participants are there altogether? (c) How many have complete data (nothing missing)? (d) What percent are in the fast track? (e) What percent took algebra 1 in h.s.? The means for the data set from 4.4 can be interpreted as how the students lean for each variable. For example, algebra 1 in h.s. mean is .79, which shows the majority of participants did take algebra 1. The same is true for each of the other variables according to the data chart. Reviewing the data shows that as the math classes continued, fewer students took the advanced courses. Math grades also leaned less than and AB average (Mason, 2013). The valid N shows the number of participants as 75 (Mason, 2013). The valid N matches all the N values for each variable showing there is no data missing. All 75 participants have complete data (Mason, 2013). 55% of participants are on the fast track (Mason, 2013). According to output 4.4, 79% of participants took algebra 1 in h.s (Mason, 2013). D3.4.5.Using Output 4.5: (a) 9.6% of what group are Asian-Americans? (b) What percent of students have visualization two scores of 6? (c) What percent had such scores of 6 or less? 6% of the participants are Asian-Americans. This is the valid percent which shows the percent of participants that do not have data missing (Mason, 2013). According to output 4.4, 5.3% of students scored a 6 on the visualization 2 test. This is seen by the percent column (Mason, 2013). The percent of students that scored a 6 or less on the visualization 2 test was 70.7%. This can be seen in the cumulative percent column in the score of 6 row (Mason, 2013). References Mason, G. A., Leech, N. L., Gloeckner, G. W., & Barrett, K. C. (2013). IBM SPSS for Introductory Statistics. ROUTLEDGE.