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According to Kirk, mode is highest score value in the data sample that has the maximum frequency of occurrence, median is the center value in the order data sample that divides the sample into two halves while mean is the average of all data points and is the center of gravity of the sample (73). Kirk highlights that the standard deviation is the most important and widely used value that helps to identify the dispersion of the data (85). The square of standard deviation is called variance. Skewness is the measure of extent to which distribution of the data leans to one side of the mean. A negatively skewed data indicates that the distribution leans to right while positively skewed data indicates distribution leaning to the left of average value. Kurtosis, on the other hand, is the measure of peakedness of the sample data. Statistics Variable1 N Valid 30 Missing 0 Mean -.0412 Median .0115 Mode 0.41 Std. Deviation .97176 Variance .944 Skewness .028 Kurtosis .600 Table 1 : Descriptive Statistics of Variable 1 The descriptive data above for Variable1 indicates that the mean value of the sample is -0.0412 with median at 0.0115 and mode being 0.41. The standard deviation of our sample variable1 is 0.97176 with variance of 0.944 which indicates that 97% of the data falls within first sigma from the mean. Our data is slightly left skewed since mean is less than median and median is less than mode. Same is indicated by value of skewness being 0.028 and the histogram below in figure 1. Histogram

shows the graphical distribution of the data. It represents the frequencies of the data sample with frequencies on y-axis while data values divided in classes on x-axis. Figure 1 : Histogram of Variable 1 The descriptive statistics of data for the second variable VAR00002 shows mean value of -0.2285 with median at -0.4288 and mode being -0.48. The standard deviation of the sample size is 1.14253 with variance of 1.305. Distribution of data in our Variable2 is right skewed since mean is greater than median and median is greater than mode as confirmed through value of skewness being -0.061 and histogram in figure 2. Statistics Variable2 N Valid 30 Missing 0 Mean -.02285 Median -0.4288 Mode -0.48 Std. Deviation 1.14253 Variance 1.305 Skewness -.061 Kurtosis -.972 Table 2 : Descriptive Statistics of Variable 2 Figure 2 : Histogram of Variable 2 According to Utts and Heckard, “a scatter plot is a two-dimensional graph of the data values in two samples representing a correlation between the two variables” (132). A scatter plot was constructed between the two variables generated using SPSS Software as shown in figure below. Here, Variable1 is placed on x-axis while Variable2 is placed on y-axis. Further, correlation analysis of the data was conducted using Pearson’s Coefficient of Correlation (0.272). Value of 0.272 for Pearson’s Coefficient of Correlation indicates a low correlation between the two variables. Since Statisticshowto website suggests High correlation: 0.5 to 1.0 or -0.5 to -1.0 Medium correlation: 0.3 to 0.5 or -0.3 to -0.5 Low correlation: 0.1 to 0.3 or -0.1 to -0.3 Pearson Correlation 0.272 Figure 3 : Scatter Plot Between Variable 1 and Variable 2 Works cited Kirk, R. Statistics : An Introduction. 5th ed. Belmont: Thomson Wadsworth, 2008. 73. Print. Statistics How

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SPSS Essay Example | Topics and Well Written Essays - 750 words. Retrieved from https://studentshare.org/statistics/1476343-spss

SPSS Essay Example | Topics and Well Written Essays - 750 words. Retrieved from https://studentshare.org/statistics/1476343-spss

(SPSS Essay Example | Topics and Well Written Essays - 750 Words)

SPSS Essay Example | Topics and Well Written Essays - 750 Words. https://studentshare.org/statistics/1476343-spss.

SPSS Essay Example | Topics and Well Written Essays - 750 Words. https://studentshare.org/statistics/1476343-spss.

“SPSS Essay Example | Topics and Well Written Essays - 750 Words”, n.d. https://studentshare.org/statistics/1476343-spss.

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