Nevertheless, we will assess the hypothesis using a two-tailed test. So according to given conditions we state that null hypothesis and alternative hypothesis will be
The scales utilized within the test instruments will be designed to denote the use of detailed statistical algorithms on the collected data. Preliminary data analysis will include descriptive statistics, which will encompass univariate analytic techniques such as means, modes, and standard deviations, and exploratory descriptive statistics, which will ascertain if the data collected, is normally distributed.
So the Pearson correlation (r) of popularity and math scores is equal to -0.368. So according to this small value of correlation coefficient, we conclude that there is a week negative association between these variables. This may imply as popularity level increases, math test scores decrease, and vice versa.
We use the correlation method to determine whether some variable that’s not under our control is associated – correlated – with another variable of our interest. Correlational studies aim at identifying relationships between variables.
So in the relationship between children’s level of popularity with their peers and their performance in academic tests they respond that there is no significant relationship between these popularity level and their maths scores.
The Descriptive procedure displays univariate summary statistics for several variables in a single table and calculates standardized values (z scores). Variables can be ordered by the size of their means (in ascending or descending order), alphabetically, or by the order in which we select the variables. Simple it is a useful procedure for obtaining summary comparisons of approximately normally distributed scale variables and for easily identifying unusual cases across those variables by computing z scores (Kinner, 2006, p.152).