Hours per day watching tvMeanStandard ErrorMedianModeStandard DeviationSample VarianceKurtosisSkewnessRangeMinimumMaximumSumCount2.320.072.001.002.154.6115.532.9720201970848Use the GSS 2018 data, shown above in Table 2, to evaluate the following.A. In the GSS 2018 data, respondents watched an average oftelevision, with a standard deviation ofhours per day ofhours.B. The standard error for population estimates of television watching in 2018 ishours.c We can be 68% confident that for 2018, the estimated hours of television watched forAmericans 18 years and older is betweenhours (lower limit) and(upperimit).D. We can be 90% confident that for 2018, the estimated hours of television watched forAmericans 18 years and older is betweenhours (lower limit) andfupperImit).E. We can be 95% confident that for 2018, the estimated hours of television watched forAmericans 18 years and older is betweenhours (lower limit) and(upperImit).F. How do these results compare with the estimates of television watching obtained by theAmerican Time Use Study? What could account for differences

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Description: Hours per day watching tvMeanStandard ErrorMedianModeStandard DeviationSample VarianceKurtosisSkewnessRangeMinimumMaximumSumCount2.320.072.001.002.154.6115.532.9720201970848Use the GSS 2018 data, shown above in Table 2, to evaluate the following.A.

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Hours per day watching tv Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count 2.32 0.07 2.00 1.00 2.15 4.61 15.53 2.97 20 20 1970 848 Use the GSS 2018 data, shown above in Table 2, to evaluate the following. A. In the GSS 2018 data, respondents watched an average of hours. hours per day of television, with a standard deviation of B. The standard error for population estimates of television watching in 2018 is hours. c We can be 68% confident that for 2018, the estimated haurs of television watched for Americans 18 years and older is between hours (lower limit) and (upper Imit).

Hours per day watching tv Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count 2.32 0.07 2.00 1.00 2.15 4.61 15.53 2.97 20 20 1970 848 Use the GSS 2018 data, shown above in Table 2, to evaluate the following. A. In the GSS 2018 data, respondents watched an average of hours. hours per day of television, with a standard deviation of B. The standard error for population estimates of television watching in 2018 is hours. c We can be 68% confident that for 2018, the estimated haurs of television watched for Americans 18 years and older is between hours (lower limit) and (upper Imit).

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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Concept explainers

Inverse Normal Distribution

The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.

Mean, Median, Mode

It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.

Z-Scores

A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.

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Question

Hours per day watching tv
Mean
Standard Error
Median
Mode
Standard Deviation
Sample Variance
Kurtosis
Skewness
Range
Minimum
Maximum
Sum
Count
2.32
0.07
2.00
1.00
2.15
4.61
15.53
2.97
20
20
1970
848
Use the GSS 2018 data, shown above in Table 2, to evaluate the following.
A. In the GSS 2018 data, respondents watched an average of
television, with a standard deviation of
hours per day of
hours.
B. The standard error for population estimates of television watching in 2018 is
hours.
c We can be 68% confident that for 2018, the estimated hours of television watched for
Americans 18 years and older is between
hours (lower limit) and
(upper
imit).
D. We can be 90% confident that for 2018, the estimated hours of television watched for
Americans 18 years and older is between
hours (lower limit) and
fupper
Imit).
E. We can be 95% confident that for 2018, the estimated hours of television watched for
Americans 18 years and older is between
hours (lower limit) and
(upper
Imit).
F. How do these results compare with the estimates of television watching obtained by the
American Time Use Study? What could account for differences

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