identified, for tension-anxiety after viewing the video three outliers were identified.
Distributions of the data variables showed that three out of the five hypotheses variables (i.e., video threat, similar news threat, and amount of news consumed) were minimally positively skewed with values ranging from .12 to .37 and platykurtic with kurtosis values ranging from -.80 to -1.14. While the kurtosis value for video threat was not noteworthy, it was nonetheless positively skewed as is evidenced especially by its histogram (see Figure 1). On the other hand, experienced tension-anxiety before and after viewing the video were more positively skewed as is also evidenced by their respective histograms (see Figure 2 and 3). Tension-anxiety before had a skewness value of 2.18, making its distribution non-normal given that the value is just outside of the +- 2.0 range, while tension-anxiety after had a skewness value of 1.54. Tension-anxiety before had a kurtosis value of 6.45 and tension-anxiety after had a kurtosis value of 2.98 making both considerably leptokurtic. In order to correct for the presence of outliers, extreme scores, skewness or kurtosis and produce normality, these three variables were transformed. The square root transformation was used for perceived threat to video because its positive skewness was moderate whereas a logarithm transformation was used for tension-anxiety before and after viewing the video due to their substantial positive skewness.
PostTest .97 23 .74
Control Group PreTest .90 21 .04
PostTest .98 21 .93
Delayed PostTest .91 21 .06
Shaphiro-Wilk’s test results and visual inspection of their histograms and normal Q-Q plots showed metaphorical language use in pre-test in experimental and control groups deviated significantly with a skewness of 2.14 (SE = .48) and a kurtosis of 3.62 (SE = .19) while Shaphiro-Wilk’s test (p < .05).
For post tests, Shaphiro-Wilk’s test (p > .05) and visual inspection of their…
III. Identify statistical tools and methods to collect data:
A. Identify Appropriate Family and Reason for Selecting it.
To analyze A-Cap Corporation’s data, I will use measures of central tendency and distribution. Measure of central tendency is a measure used to describe the mean, median, and mode of a particular set of data while measure of distribution shows the skewness, kurtosis, and develops a hypothesis about a particular set of data. The reason I selected these two measures is that they…
from each other, and within each sample, the observations are sampled randomly and independently of each other.
2. The visual interpretation of the histogram is that there is a positive kurtosis and a negative skewness.
N Minimum Maximum Mean Std. Deviation Skewness Kurtosis
Statistic Statistic Statistic Statistic Statistic Statistic Std. Error Statistic Std. Error
quiz3 105 0 10 8.05 2.322 -1.177 .236 .805 .467
Valid N (listwise) 105
Std. Error of Skewness .011 .011
Kurtosis -1.018 12.307
Std. Error of Kurtosis .022 .022
Range 2 53
Minimum 1 1
Maximum 3 54
Sum 85073 187527
Percentiles 25 1.00 2.00
50 1.00 3.00
75 2.00 5.00
AGE is a categorical variable, which signifies that mode will be an appropriate measure of central tendency. The mode for the variable AGE is 1, which signifies that majority of the respondents fall in the age group of 18-35 years.
Since the ADULTCT variable, measured at ratio level, is…
on the project. Figure 7 again displays our conceptual model, but with the accompanying variable measures described above.
We use linear regression for model and hypothesis testing and SPSS, version 23, to run all tests. To begin with, we tested for the assumptions of linear regression including linearity, multicollinearity, homoscedasticity, and normality. We computed and analyzed the descriptive statistics for all variables, including the skewness and kurtosis statistic as…
respondent-nonrespondent check for response bias. (Saunders, 2009)
3.12.4: Normality test
Normality is defined as the shape of data distribution, (hair et al 2006) the violation of the normality test can affect the estimation process or interpretation of results for example in analysis of SEM by increasing the chi-square value (hair et al 2006).Normality test for the data sets will be conducted using SPSS v.22 to ensure that the parametric data are normally distributed. Skewness and Kurtosis…
Kurtosis is a statistical measure used to describe the distribution of observed data around the mean.
Descriptive statistics do not enable us to make conclusions beyond the data we have analysed or reach conclusions regarding any inference we might have made.
Measures of variability are another important technique used in descriptive statistics. These measures define the methods of summarizing a group of data by describing how spread out the data is.
To describe this spread, a number of…
Through reviewing the minimum, maximum, and range of values I attempted to discern and identify potential coding errors as well as invalid data. The nature and distribution of the values were explored through examining the mean, standard deviation, and variance as well as skewness and kurtosis. For example, the variable Age contained 320 valid cases, with respondents ranging in age from 18 to 35 years. The mean age was 28.02 years with a standard deviation of 4.76 years. Emailtime and Wwwtime…
Summary of Results
The predictor variable, I would apply for a job with a female CEO or boss, had a skewness of -2.54 and a kurtosis of 4.57. The predictor variable, I would vote for a female president, had a skewness of -2.43 and a kurtosis of 5.57. The spearman’s correlation between the predictor variable, I would apply for a job with a female CEO or bass and the outcome variables, IAT scores, was 0.075 and had a significance of 0.726. The spearman’s correlation between the predictor…