TABLE 4 F DISTRIBUTION Area or probability Entries in the table give F values where α 1s the area or probability in the upper tail of the F distribution. For example, with 4 numerator degrees of freedom. 8 denominator degrees of freedom, and a .05 area in the upper til, Fs 3.84. Denominat tor Degrees of Freedom Numerator Degrees of Freedom Tai 15 10 60 100 9864950 5359 55.83 57.24 58.20 58.9 5944 5986 60.19 61.22 61.74 62.05 62.26 62.53 62.79 630 63.30 161.45 199.50 215.71 224.58 230.16 233.99 236.77 238.88 240.54 241.88 245.95 248.02 2匉.26 250.10 251.14 252.20 253.04 254.19 025 647.79 9948 64.15 89960 92183 37.948.20 95664 963.28 96863 98487 993.08 998.09 100140 1005.60 1009.79 1013.16 1017.76 01 4052.18 4999.34 5903.53 5624.26 5763.96 5858.95 5928.33 5980.95 6022.40 6055.93 6156.97 6208.66 6239.86 626035 6286.43 6312.97 6333.92 636280 9.38 949 1851 19.00 9.16 19.25 1930 19.33 19.35 19.37 19.38 1940 1943 19,45 1946 1946 19,47 1948 1949 1949 385 39.00 39.17 39.25 39.3039.33 39.36 3937 39.39 3940 3943 39,45 3946 3946 39.47 3948 3949 3950 98.50 99.00 99.16 99.25 99.30 9933 99.36 99.38 99.39 9940 9943 99.45 9946 99.47 99.48 9948 9949 99.50 8.53 9.00 9.29 9.37 9.39 942 946 948 9.24 9.35 945 947 025 5.39 9.28 5.28 8.94 5.27 8.89 5.24 5.23 8.79 5.20 8.70 5.18 10.13 1744 1604 5.44 5.10 1488 14.7314.62 14.54 14.47 442 14.251417 4.12 1408 14.04 13.99 13.96 13.91 34.12 3082 2946 28.71 28.24 27.9 277 2749 27.34 27.23 2687 2669 26.58 26.50 26.41 26.32 2624 26.14 8.63 8.62 8.59 8.57 8.55 8.85 4.54 7.7 3.98 609 3.95 6.04 3.94 6.00 8.90 3.92 5.96 3.83 3.79 569 8.36 3.8413.75 1365 13.58 13.47 3.78 5.66 3.76 5.72 5.80 8.56 6.26 5.75 6.94 12.22 105 6.59 5.86 8.50 21.20 18.00 1669 15.98 5.52 5. 4.98 14.80 14.66 14.55 4.20 14.02 3.91 01 i0 05 3.324 3.21 4.56 6.33 9.55 4.52 6.27 945 4.50 6.23 9.38 4.46 443 10.0 6,26 3.27 2.06 39 10.97 1067 1046 09 0,16 10,05 6,76 6,08 9.29 01 9.20
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.
In exercise 12, the following data on x = average daily hotel room rate and y = amount spent on entertainment (The Wall Street Journal, August 18, 2011) lead to the estimated regression equation ŷ = 17.49 + 1.0334x. For these data SSE = 1541.4.
Click on the datafile logo to reference the data. Use Table 1 of Appendix B.
a. Predict the amount spent on entertainment for a particular city that has a daily room rate of $89 (to 2 decimals).
$
b. Develop a 95% confidence interval for the mean amount spent on entertainment for all cities that have a daily room rate of $89 (to 2 decimals).
$ to $
c. The average room rate in Chicago is $128. Develop a 95% prediction interval for the amount spent on entertainment in Chicago (to 2 decimals).
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