2 pages/≈550 words
Accounting, Finance, SPSS
Statistical Analysis Using SPSS Software: GSS14SSDS-A.sav Dataset (Statistics Project Sample)
Statistical Analysis Students Name University Name Statistical Analysis Statistical analysis is usually carried out on a sample data in order to find the underlying trend and parameters of the data. When analyzing data, visual presentations are very important in understanding the spread of data and its feature. We also employ statistical test in defining the variation contained within the data. Therefore, this analysis will base focus on the GSS14SSDS-A.sav dataset. The analysis will be performed using SPSS software. In our analysis, we will employ the CHILDS (number of children) variable and the SIBS (number of siblings) variable in order to find out if the two have a significant statistical relationship existing between the two. In this analysis, we define CHILDS variable as the dependent variable while the SIBS variable will be the independent variable. Regression analysis will be performed in order to know whether the dependent variable can be predicted using the predictor variable. Below are the results. Above are the descriptive statistics. From the sampled subjects, on average, each has on average an at most two children with at most four siblings. The sample size was of, n=1494. The results indicated that, from the sample, the highest number of children a family could have is 8 (maximum=8) with some indicating that they had no children (minimum=0). Additionally, the highest number of siblings a family could have is 23 (maximum=23) with some indicating that they had no siblings (minimum=0). From the above scatterplot and the correlation analysis, we can see that there is a small positive and weak correlation between the two variables. This is indicated by the Pearson’s correlation coefficient, r=0.247 and can be said to be significant at 0.01 level of significance. Therefore, we can assert that there is a relative small relationship that exists between the number of children a respondent has and the number of brothers and sisters s/he has. Regression analysis will be employed in order to determine if the predictor variable contributes to the variation within the dependent variable and to determine if the dependent variable can be predicted using the predictor variable. The results are as below. From the above analysis, we have the coefficient of determination as, r2=0.061. Only 6.1% of the variation within the dependent variable (number of children a responded has) is explained by t...
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