Use for questions 1-5: An imaging scientist wishes to determine whether the intensity of light has an effect on the ability of their algorithm to recognize a particular target. Considering only daytime recognition, the scientist classifies the light source as being high or low intensity and performs a series of randomly chosen recognition tests. The outcome of each test is either positive (recognized) or negative (not recognized). The following data is observed: High Intensity Low Intensity Positive Recognition 36 9 Negative Recognition 24 31 We will conduct a Chi-Square Test of Independence at the 5% level of significance. What are the null and alternative hypotheses. O A. Ho: The two variables are not independent of each other. Ha: The two variables are independent of each other. O B. Ho: The observed count data does not fit the given distribution. Ha: The observed count data fits the given distribution. OC. Họ: The observed count data fits the given distribution. Ha: The observed count data does not fit the given distribution. O D. Ho: The two variables are independent of each other. Ha: The two variables are not independent of each other. QUESTION 2 What is the EXPECTED COUNT for the cell that has 36 in it (Positive and High)? The answer is an integer. 27 QUESTION 3 What is the Chi-Square Contribution for the cell with 36 (positive and high)? The answer is an integer.
Use for questions 1-5: An imaging scientist wishes to determine whether the intensity of light has an effect on the ability of their algorithm to recognize a particular target. Considering only daytime recognition, the scientist classifies the light source as being high or low intensity and performs a series of randomly chosen recognition tests. The outcome of each test is either positive (recognized) or negative (not recognized). The following data is observed: High Intensity Low Intensity Positive Recognition 36 9 Negative Recognition 24 31 We will conduct a Chi-Square Test of Independence at the 5% level of significance. What are the null and alternative hypotheses. O A. Ho: The two variables are not independent of each other. Ha: The two variables are independent of each other. O B. Ho: The observed count data does not fit the given distribution. Ha: The observed count data fits the given distribution. OC. Họ: The observed count data fits the given distribution. Ha: The observed count data does not fit the given distribution. O D. Ho: The two variables are independent of each other. Ha: The two variables are not independent of each other. QUESTION 2 What is the EXPECTED COUNT for the cell that has 36 in it (Positive and High)? The answer is an integer. 27 QUESTION 3 What is the Chi-Square Contribution for the cell with 36 (positive and high)? The answer is an integer.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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Related questions
Question

Transcribed Image Text:QUESTION 1
Use for questions 1-5: An imaging scientist wishes to determine whether the intensity of light has an effect on the ability of their algorithm to recognize a particular target. Considering only
daytime recognition, the scientist classifies the light source as being high or low intensity and performs a series of randomly chosen recognition tests. The outcome of each test is either positive
(recognized) or negative (not recognized). The following data is observed:
High Intensity Low Intensity
Positive Recognition
36
9.
Negative Recognition
24
31
We will conduct a Chi-Square Test of Independence at the 5% level of significance.
What are the null and alternative hypotheses.
A. Ho: The two variables are not independent of each other.
Ha: The two variables are independent of each other.
O B. Ho: The observed count data does not fit the given distribution.
Ha: The observed count data fits the given distribution.
O C. Ho: The observed count data fits the given distribution.
Ha: The observed count data does not fit the given distribution.
D. Ho: The two variables are independent of each other.
Ha: The two variables are not independent of each other.
QUESTION 2
What is the EXPECTED COUNT for the cell that has 36 in it (Positive and High)? The answer is an integer.
27
QUESTION 3
What is the Chi-Square Contribution for the cell with 36 (positive and high)? The answer is an integer.
3
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