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In the first paragraph of its quantitative chapter 4, the result chapter remained the research questions that are examined. This is reminiscent of the reader what you will investigate after you have passed through the details of your methodology. It is also helpful that the reader knows what the variables will be analyzed.
Specify a paragraph that shares the reader how to clean the data. Did you remove univariate or multivariate outliers? How will you treat missing data? What is your definitive sample size?
The next paragraph should describe the example with demographic and research variables. Provision of frequencies and percentages for graves of the nominal and ordinal level and means and means and standard deviations for scale variables. You can deploy this information in numbers and tables.
frequencies and percentages. The most commonly observed category of Cardio was Yes ( n = 41, 72%). The most commonly observed category of the shock was no ( n = 34, 60%). Frequencies and percentages are shown in Table 1.
summary statistics. The observations for Minicog had an average of 25.49 ( SD = 14.01, se m = 1.87, min = 2.00, max = 55.00). The observations for digitally had 29.12 ( SD = 10.03, se m = 1.33, min = 15.50, max = 48.50). The inclinedness and kurtosis were also calculated in Table 2. If the shaftness greater than 2 is in absolute value, the variable is considered asymmetrical about its average. If the kurtosis is greater than or equal to 3, the distribution of the variables differs significantly as a normal distribution in their tendency to produce outliers (Westfall & Henning, 2013).Now, since the data has been made clean and descriptions, turn to the execution of the statistics and assumptions of these statistics for the research question 1. First place the assumptions, then the results of the statistics. Have a clear acceptance or rejection of the hypothesis statement when you have one. Here is an independent T-test example of Samples:
Introduction. A two-tailed sample T test was performed to investigate whether the mean of Minicog was different between the NO and JA categories of Cardio.
assumptions. The assumptions of the normality and the homogeneity of the variance were evaluated.
normality. A Shapiro Wilk test was performed to determine if Minicog could be generated by a normal distribution (Razali & WAH, 2011). The results of the Shapiro Wilk test were significant, w = 0.94, p = .007. These results suggest that Minicog has unlikely been generated by a normal distribution; Thus, normality can not be accepted. However, the average of any random variables is approximately normally because the scan size rises according to the central boundary attachment (CLT). Therefore, with a sufficiently large sample size ( n > 50) deviations from normal nature have little impact on the results (Stevens, 2009). An alternative way to test the adoption of normality was used by calling the quantities of the model residues against the quantities of a CHI-square distribution, also referred to as Q-Q Scatterplot (Decarlo, 1997). For the acceptance of the normality to be achieved, the quantals of the residuen must not deviate from the theoretical quantile. Strong deviations can specify that the parameter estimates are unreliable. Figure 1 shows a Q-Q scatterplot from Minicog.
homogeneity of the variance. LevГ©e Test Equality The variance was used to assess if the homogeneity of the variance acceptance was met (Levene, 1960). The homogeneity of the deviation acceptance requires that the deviation of the dependent variables in each group is approximately the same. The result of Levenes test was significant, f (1, 54) = 18.30, p
Perform statistics and assumptions for your other research questions in the next paragraphs. Assumptions first, then first the results of the statistics with suitable tables and figures.
Paste sure that you add all in-text quotes to your reference section. Here is a sample of references.
Conover, W. J., & Iman, R. L. (1981). Rank transformations as a bridge between parametric and non-parametric statistics. The American statisticians, 35 (3), .
decarlo, L. T. (1997). More importance and use of kurtosis. Psychological Methods, 2 (3), .
Levene, H. (1960). Contributions to probability and statistics. Essays in honor of Harold Hoteln, I. Olkin et al. Eds., Stanford University Press, .
razali, N.M., & Wah, Y. B. (2011). Characteristics of Shapiro-Wilk, Kolmogorov-Smirnov, Lillafors and Anderson Darling Tests. Journal of Statistical Modeling and Analysis, 2 (1), 21-33.
Ruxton, G. D. (2006). The unequal variance T-Test is an uninterrupted alternative to the T-Test of the student and the man whitney U test. behavioral ecology, 17 (4), .
Intelligentus statistics [online computer software]. (2019). Retrieved from ouressays.com /
Stevens, J.P. (2009). used multivariate statistics for social sciences (5. Ed.). Mahwah, NJ: Routledge Academic.
Westfall, P. H., & Henning, K.S. (2013). Texts in Statistical Science: Experience Advanced Statistical Methods. Boca Raton, FL: Taylor & Francis.