Movie Theater Attendance The data shown are the weekly admissions, in millions, of people attending movie theaters over three different time periods. At α=0.01, is there a difference in the means for the weekly attendance for these time periods? Use the critical value method with tables.1950-19741975-19901991-200056.716.322.838.318.226.026.018.828.118.920.526.819.923.925.216.525.627.7 Assume that all variables are normally distributed, that the samples are independent, that the population variances are equal, and that the samples are simple random samples, one from each of the populations.

For the given data perform Perform Anova single factor

Answered: Movie Theater Attendance The data shown…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Movie Theater Attendance The data shown are the weekly admissions, in millions, of people attending movie theaters over three different time periods. At α=0.01, is there a difference in the means for the weekly attendance for these time periods? Use the critical value method with tables.

1950 - 1974	1975 - 1990	1991 - 2000
56.7	16.3	22.8
38.3	18.2	26.0
26.0	18.8	28.1
18.9	20.5	26.8
19.9	23.9	25.2
16.5	25.6	27.7

Assume that all variables are normally distributed, that the samples are independent, that the population variances are equal, and that the samples are simple random samples, one from each of the populations.

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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