I need help with this problem Conduct a hypothesis test about the mean cost per square foot at a chosen significance level. Reference an internet source for the current average (or median) cost per square foot of homes in Orange County.Discuss/explain your choice of significance level for your hypothesis test in #1 as it relates to the power of a test and Type I/II errors. 10% upper critical value in units of data = 156918Sample MeanStd Error1.55108e+06Test is significant at 10% level.-1500000121965TNull density (in units of data): Student t; mean = 0.3, scale = 121965, df = 169Alternative Hypothesis Ha: Mean of 'List.Price' is greater than 0.3Observed Data ScaleObst Stat12.7174TT-500000 0 500000Sample Mean [List.Price]P-value Graph: t-Test▲ Obs Sample Mean = 1551078P-Value = 9.9924e-27DF1500000169-10t Distribution Scale (df = 169)10% t-Upper Critical1.28658T-5T0▲ Obst Stat = 12.717P-Value = 9.9924e-27t-Values510P-value9.99239e-27

Given Information: Consider the results from the given output: Sample Mean Std error Observed t-statistics DF 10% t-upper critical p-value 1551080.00 121965 12.7174 169 1.28658 0.00000001. The null and alternative hypotheses are: H0: μ=0.3Ha:μ>0.3 The level of significance is 0.10 The observed test statistic is given as 12.7174 The critical value is given as 1.28658. The p-value is given as 0.000000 Decision criterion: Reject the null hypothesis p≤0.10Otherwise fail to reject the null hypothesis Conclusion: Since the p-value is 0.000 which is less than the significance level of 0.10. Hence, the null hypothesis gets rejected at a 10% level of significance. Hence, we can conclude that mean of the list price is greater than 0.3.2. Type I error occurs when the null hypothesis gets rejected when it is actually true. Type II error occurs when the researcher fails to reject the null hypothesis when it is false. The probability of committing the Type I error is known as the significance level. In our hypothesis test, the significance level is 0.10. Our chosen significance level relates to the probability of Type I error. The probability of not committing a Type II error is called a Power of a hypothesis test. The quantity 1-β is called Power.

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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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I need help with this problem

Conduct a hypothesis test about the mean cost per square foot at a chosen significance level. Reference an internet source for the current average (or median) cost per square foot of homes in Orange County.
Discuss/explain your choice of significance level for your hypothesis test in #1 as it relates to the power of a test and Type I/II errors.

10% upper critical value in units of data = 156918
Sample Mean
Std Error
1.55108e+06
Test is significant at 10% level.
-1500000
121965
T
Null density (in units of data): Student t; mean = 0.3, scale = 121965, df = 169
Alternative Hypothesis Ha: Mean of 'List.Price' is greater than 0.3
Observed Data Scale
Obst Stat
12.7174
T
T
-500000 0 500000
Sample Mean [List.Price]
P-value Graph: t-Test
▲ Obs Sample Mean = 1551078
P-Value = 9.9924e-27
DF
1500000
169
-10
t Distribution Scale (df = 169)
10% t-Upper Critical
1.28658
T
-5
T
0
▲ Obst Stat = 12.717
P-Value = 9.9924e-27
t-Values
5
10
P-value
9.99239e-27

Definition Definition Middle value of a data set. The median divides a data set into two halves, and it also called the 50th percentile. The median is much less affected by outliers and skewed data than the mean. If the number of elements in a dataset is odd, then the middlemost element of the data arranged in ascending or descending order is the median. If the number of elements in the dataset is even, the average of the two central elements of the arranged data is the median of the set. For example, if a dataset has five items—12, 13, 21, 27, 31—the median is the third item in ascending order, or 21. If a dataset has six items—12, 13, 21, 27, 31, 33—the median is the average of the third (21) and fourth (27) items. It is calculated as follows: (21 + 27) / 2 = 24.

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