Skewness

Histograms: Both histograms are unimodal (have one mode). As the mean of hours of TV viewed per week is (30.438) which is to the right of the median (30), this indicates a positive skewness. For household debt, the mean (126471.342) is to the left of the median (127318), which indicates a negative skewness. The hours of TV viewing per week appear to be moderately correlated with the level of household debt. There is a more significant disconnection with the families that view between 30-42

2: Discussion Interpretation of findings Table 1.2 Descriptive Summary Statistics for the independent variable age age Mean 57.62 Standard Error 2.299936 Median 58.5 Mode 58 Standard Deviation 16.263 Sample Variance 264.4853 Kurtosis -0.65102 Skewness -0.22511 Range 69 Minimum 22 Maximum 91 Sum 2881 Count 50 The variable age is the independent variable and is of a ratio level of measurement (Loiselle et al., 2011). The measure of central tendency to describe age in table 1.2 are the mean of 57

meet these criteria, meaning that the chi-squared test in this circumstance would be inappropriate. To avoid such issues, the nonparametric Kolmogorov-Smirnov test was used in preference as it has less rigorous data requirements.. The positive skewness values for FP89 (1.285) indicate that the sample is positively skewed compared to a normal (Gaussian) distribution, with a long right tail. The kurtosis value is 2.013, compared to a normal distribution which would have a Kurtosis value of 0.00.

For my project I chose to look at the Albany Devils first 30 games of 2016. I chose this topic because my parents have season tickets to Albany Devils games and I either go to them when I am home or watching them on my laptop when I am at school. My elements where the first 30 games of 2016 like stated before, and my variables were goals for, goals against, the result of the game and the distance traveled. The elements are listed by the day and I also listed who the opponent was so one can tell if

The variable age is the independent variable and is a ratio level of measurement (Loiselle et al., 2011). The measure of central tendency to describe age are in table 1.2 are the mean of 57.62 which is the average age, the median which is the middle score within the distribution when all scores are organized of 58.5 and the mode of 58 which is the most frequently occurring age (Loiselle et al., 2011). The measures of variability are the range of 69 with a minimum age of 22 and a maximum age of 91

Statistics Course Project Part 1 Student: Zissis Koukoutaris Course : Statistics Professor: Dimitrios Fotiadis Semester: Fall-2012 Introduction This report is written by Koukoutaris Zissis a student from Northeastern University. Mr Fotiadis my professor of the MGSC 23021 assigned me the task. 1. Use methods of descriptive statistics to summarize the data. Comment on the findings 2. Develop estimated regression equations, first using annual income as the independent variable

more detail when descriptive statistics for the same is calculated. Descriptive Statistics: Net Worth Ranges Mean 3.222581 Standard Error 0.44208 Median 3.4 Mode 3.8 Standard Deviation 2.461397 Sample Variance 6.058473 Kurtosis 4.226665 Skewness 1.595086 Range 11.7 Minimum 0.3 Maximum 12 Sum 99.9 Count 31 In the above descriptive statistics we can see that both

The following is an examination of the descriptive and inferential statistics of the questions asked on the XYZ Sporting Goods Company’s national survey of college-aged recreation runners on a variety of issues of potential interest to a launch of a new shoe product line. Descriptive Statistics The following are the descriptive statistics for the questions on XYZ Sporting Goods Company’s survey on a potential new shoe product launch. Continuous variables may also contain inferential

The first step is to access the data, which can be found at Sports Reference LLC (2000-2012). Then the data is tabulated columnwise, here into Microsoft Excel but that is not necessary. Double checking against Yahoo! Sports (2012) verifies the data is correct, quickly by counting total number and then by checking that the 150th and 180th scores are the same, which they are. What this checking accomplishes is to reveal "n," the number of entries, which will be necessary describing these results. This

The researchers wanted to test if the shot or nasal spray were more effective against the flu. The null hypothesis would be that both types of vaccine would have the same effect. The alternative hypothesis would be that one was more effective than the other making this a two-tailed test. In this case the P value was less than alpha so you would reject the null hypothesis. The results were statistically significant because the numbers were less than P, however the example doesn’t tell me what test