Does the color of your team uniform affect your performance? That's what researchers in England claimed, after studying data from 68 soccer teams over 56 seasons. On average, teams wearing red won 54.5%, of their home games; blue won 50.9%, white won 52.0%, and teams wearing yellow won only 47.3%. The researchers compared the performance of teams wearing four different color groups (blue, yellow, red, white). You have seen two groups compared before, but how do we compare means across four different groups? The data can be found in the Download .csv file. Use a = 0.05 for any statistical tests. (a) Perform Levene's test of common variance (homoscedasticity) and report the P-value. P-value= (use three decimals). (b) Complete the following one-way ANOVA table. (for each entry use three decimals). Source P-value DF MS Between |田 Within a) larger than b) smaller than c) the exact same as d) not statistically different than total (c) Perform a Tukey HSD, Post Hoc analysis. Use a 95% confidence level. When looking at the difference: Hyellose-HBlue the lower limit for the difference is # (use four decimals) and the upper limit is (use four decimals). Based on the data the winning proportion of first colour listed is ? v then the second color listed. a) yes (d) Based only on the correct ANOVA and Post Hoc analysis of the above data, does the colour of jersey influence the outcome? ? b) no
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Please use R-Studio if possible. Thank you in advance!
Data:
Blue |
54.73 |
54.92 |
51.81 |
46.02 |
48.73 |
51.06 |
46.04 |
52.92 |
48.75 |
51.79 |
53.69 |
54.42 |
52.18 |
50.03 |
50.33 |
52.36 |
46.54 |
50.11 |
53.19 |
51.56 |
48.77 |
52.8 |
48.96 |
Red |
53.88 |
59.14 |
57.13 |
54.72 |
55.66 |
54.85 |
53.35 |
55.96 |
53.69 |
50.39 |
53.15 |
51.73 |
57.28 |
51.33 |
54.65 |
55.57 |
White |
50.85 |
55.75 |
52.85 |
56.73 |
49.89 |
49.45 |
52.63 |
51.96 |
50.88 |
50.37 |
50.22 |
Yellow |
48.88 |
50.69 |
47.61 |
46.52 |
45.27 |
46.12 |
46.51 |
43.76 |
46.98 |
46.41 |
49.42 |
42.26 |
55.73 |
47.85 |
48.33 |
51 |
43.26 |
44.15 |
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