Professional descriptive statistics assignment help provided by top-class experts

Descriptive statistics is a branch of statistics where we are simply describing the data. Most of the assignments that we handle will, at some point, require us to provide descriptive statistics of the data. If you are looking for a place where to get professional descriptive statistics assignment help, then contact us. We have immense experience in handling such tasks. Here is one such solution that we have prepared as a demonstration of the services that we offer. The data used by the expert is secondary data collected from university students with different years of school experience. Help with descriptive statistics assignment on understanding the nature of the data For any help with the descriptive statistic assignment that we offer to students, it's essential that we understand the nature of the data at hand before we begin preparing the solutions. This is simply understanding the variables in the data. The definition of the variables and their scale of measurement is given below Gender: The sex of the student (Male and Female). The scale of measurement of Gender is Nominal. GPA: The grading point average for each student. The scale of measurement of GPA is Ratio because GPA has true zero property Final: The final aggregate score for each student. The scale of measurement of the final is also the Ratio Correlation that measures the linear relationship between variables. The type of correlation that exists between each variable is illustrated below;

The sample size of the data set is 105 Descriptive Statistics Homework Help on Correlation Assumptions of Correlation between GPA and final Since the two variables are continuous, it's appropriate to use Pearson's correlation. The following are Pearson's correlation assumptions.

The two variables should be continuous

The two variables are continuous variables, and so, the first assumption is met

The variables should be normally distributed.

In order to test for this assumption, we use the Shapiro-Wilk test of normality whose null hypothesis is-the variables are normally distributed when the p-value is less than 0.05

Normality test

The final score Shapiro-Wilk has a p-value greater than 0.05; therefore, our descriptive statistics homework helper concludes that the final scores of students are normally distributed.

Histograms

Histogram

The two histograms are said to be approximately normal and leptokurtic.

Descriptive Statistics Statistics

The skewness values for both GPA and final (-0.457 and -0.335 respectively) falls between -0.5 and 0.5. We, therefore, conclude that the distributions of the two variables are approximately symmetric, that is, they are normally distributed. The kurtosis values for both GPA and final (-0.458 and -0.332 respectively) are less than 0, and we, therefore, conclude that the variables are platykurtic, the is, histograms have a shorter and thinner tail with a lower and broader central peak.

Scatter Plot

The scatterplot shows that there is a positive linear relationship between the student's GPA and their final score. That is, as the student's GPA increases, their final score also increases. Other Assumptions of correlation are;

Linearity

The scatter plot displayed linearity in the variables. The linearity assumption is met

There should be no significant outliers.

The scatter plot obtained above shows that there is no unusual data point, and hence, the outlier's assumption is also met. All four correlation assumptions are met for the regression between the two variables. The variables are both continuous; the scatter plot reveals the linearity of the variable and the absence of outlier. The histogram plot also shows that the two variables are approximately normal. Relationship testingby online descriptive statistics tutors Research Question: Is there a significant linear relationship between the student's GPA and the final score.

Hypothesis

H0: There isn't a significant linear relationship between the student's GPA and the final score H1: There is a significant linear relationship between the student's GPA and the final scores

Rejection Rule

Reject if H0 is p-value>0.05 The table below gives the correlation matrix of the variables of interest. Correlations

The lowest magnitude correlation in the intercorrelation matrix is between the student's gender and their final score r(105) = -0.0140, p =0.156. The p-value is greater than 0.05; we can conclude that a significant linear relationship between the student's gender and their final score exists. The highest magnitude correlation in the intercorrelation matrix is the students GPA and the final score r(105) = 0.223 p =0.022. The p-value is less than 0.05, and we can conclude that a significant linear relationship between the student's GPA and their final score exists. The correlation between GPA and final is r(105) = 0.223 with p-value =0.022. We conclude that a significant linear relationship between the student's GPA and their final score exists. We are interested in determining whether it is a linear relationship (association) between the student's GPA and final. To ascertain this, we establish the H0 that a significant linear relationship between the variables does not exist. The correlation analysis was performed, and the value was obtained to be r(105) = 0.223 p =0.022. We conclude that a significant linear relationship between the students' gender and their final score does not. This answers the research question that our online descriptive statistics tutor was seeking answers to. The correlation coefficient of 0.233 between GPA and final indicates a weak positive linear relationship between the GPA and final. Short Conclusion on Descriptive Statistics Homework Help For this descriptive statistics homework help, correlational research can't prove that one variable is the cause of fluctuation in the other variable, or in simple terms, correlation isn't equal to causation.