Descriptive Statistics Application Exercise Essay Examples
Type of paper: Essay
Topic: Education, Square, Evidence, Relationships, Value, Output, Significance, Students
We begin the discussion of descriptive statistics from Frequencies table. It shows that there are 7 variables are used:
There are 15 observations of each variable, no values are missed. According to the frequency tables, first five variables are binomial variables (only two possible values), sixth variable has 4 different values and 7th – 3 possible values.
Consider a cross tab of JobPreparation and ProfessionalDevelopment. There are 9 observations have JobPreparation=1 and ProfessionalDevelopment=1, one observation is with JobPreparation=1 and ProfessionalDevelopment=2, three observations are with JobPreparation=2 and ProfessionalDevelopment=1 and 2 observations are with JobPreparation=2 and ProfessionalDevelopment=2.
According to Chi-Square tests output, Pearson Chi-square is equal to 1.875 with p-value of 0.242. Since the testing is performed with the level of significance of 0.05, we failed to reject the null hypothesis and we have no evidence to say that FCS graduate program offer workshops and professional development (at 5% level of significance).
The next crosstab is computed for JobPreparation and MembershipMeetings. According to the Chi-square tests output, Pearson Chi-Square is 1.25 with 2-sided p-value of 0.329. Since p-value is higher than 0.05, we failed to reject the null hypothesis. We have no evidence to say that CS graduate program has prepared a candidate for a job in his field (at 5% level of significance).
Correlations table. There is strong positive linear relationship between PrepareToGetJob and FacilitatedProfessionalDevelopment (r=0.746, p=0.001). There is moderate positive linear relationship between PrepareToGetJob and CourseTopicsRelevant (r=0.522, p=0.046). There is also insignificant relationship between FacilitatedProfessionalDevelopment and CourseTopicsRelevant (r=0.501, p=0.057).
T-test output. According to Levene’s test for equal variances, we consider, that variances are equal. According to independent samples t-test, there is no evidence to say that there is a significant difference between mean values of PrepareToGetJob samples divided by JobPreparation factor.
For FacilitatedProfessionalDevelopment divided by ProfessonalDevelopment factor, Levene’s test reports that variances are not equal, independent samples t-test is insignificant, difference between means is insignificant.