The chi-squared goodness-of-fit test can be used to test if data comes from a specific continuous distribution by binning the data to make it categorical. Using the OpenIntro Statistics county_complete dataset, test the hypothesis that the persons_per_household 2019 values come from a normal distribution with mean and standard deviation equal to that variable's mean and standard deviation. Use signficance level a = 0.01. In your solution you should 1. Formulate the hypotheses 2. Fill in this table Range (-⁰⁰, 2.34] (2.34, 2.81] (2.81, 3.27] (3.27,00) Observed 802 Expected 854.2 The first row has been filled in. That should give you a hint for how to calculate the expected frequencies. Remember that the expected frequencies are calculated under the assumption that the null hypothesis is true. FYI, the bounderies for each range were obtained using JASP's drag-and-drop cut function with 8 levels. Then some of the groups were merged. 3. Check any conditions required by the chi-squared goodness-of-fit test. 4. Calculate the p-value. Show how you did it. I recommend using this Desmos page, which is a little better than the Desmos page linked in the notes. You can link a screenshot or the entire Desmos page. 5. Complete the test with a conclusion stated in the context.
The chi-squared goodness-of-fit test can be used to test if data comes from a specific continuous distribution by binning the data to make it categorical. Using the OpenIntro Statistics county_complete dataset, test the hypothesis that the persons_per_household 2019 values come from a normal distribution with mean and standard deviation equal to that variable's mean and standard deviation. Use signficance level a = 0.01. In your solution you should 1. Formulate the hypotheses 2. Fill in this table Range (-⁰⁰, 2.34] (2.34, 2.81] (2.81, 3.27] (3.27,00) Observed 802 Expected 854.2 The first row has been filled in. That should give you a hint for how to calculate the expected frequencies. Remember that the expected frequencies are calculated under the assumption that the null hypothesis is true. FYI, the bounderies for each range were obtained using JASP's drag-and-drop cut function with 8 levels. Then some of the groups were merged. 3. Check any conditions required by the chi-squared goodness-of-fit test. 4. Calculate the p-value. Show how you did it. I recommend using this Desmos page, which is a little better than the Desmos page linked in the notes. You can link a screenshot or the entire Desmos page. 5. Complete the test with a conclusion stated in the context.
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.4: Distributions Of Data
Problem 3GP
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![The chi-squared goodness-of-fit test can be used to test if data comes from a specific continuous distribution by binning the data to make it
categorical.
Using the OpenIntro Statistics county_complete dataset, test the hypothesis that the persons_per_household 2019 values come from a normal
distribution with mean and standard deviation equal to that variable's mean and standard deviation. Use signficance level a = 0.01.
In your solution you should
1. Formulate the hypotheses
2. Fill in this table
Range
(-⁰⁰, 2.34]
(2.34, 2.81]
(2.81, 3.27]
(3.27,00)
Observed
802
Expected
854.2
The first row has been filled in. That should give you a hint for how to calculate the expected frequencies. Remember that the expected
frequencies are calculated under the assumption that the null hypothesis is true.
FYI, the bounderies for each range were obtained using JASP's drag-and-drop cut function with 8 levels. Then some of the groups were
merged.
3. Check any conditions required by the chi-squared goodness-of-fit test.
4. Calculate the p-value.
Show how you did it. I recommend using this Desmos page, which is a little better than the Desmos page linked in the notes. You can link
a screenshot or the entire Desmos page.
5. Complete the test with a conclusion stated in the context.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F7884aebb-abc9-4ae2-aee8-88ec2e400645%2Ff5b42f4d-6fdb-457d-a6cf-b812d27130ca%2Facx9o7_processed.jpeg&w=3840&q=75)
Transcribed Image Text:The chi-squared goodness-of-fit test can be used to test if data comes from a specific continuous distribution by binning the data to make it
categorical.
Using the OpenIntro Statistics county_complete dataset, test the hypothesis that the persons_per_household 2019 values come from a normal
distribution with mean and standard deviation equal to that variable's mean and standard deviation. Use signficance level a = 0.01.
In your solution you should
1. Formulate the hypotheses
2. Fill in this table
Range
(-⁰⁰, 2.34]
(2.34, 2.81]
(2.81, 3.27]
(3.27,00)
Observed
802
Expected
854.2
The first row has been filled in. That should give you a hint for how to calculate the expected frequencies. Remember that the expected
frequencies are calculated under the assumption that the null hypothesis is true.
FYI, the bounderies for each range were obtained using JASP's drag-and-drop cut function with 8 levels. Then some of the groups were
merged.
3. Check any conditions required by the chi-squared goodness-of-fit test.
4. Calculate the p-value.
Show how you did it. I recommend using this Desmos page, which is a little better than the Desmos page linked in the notes. You can link
a screenshot or the entire Desmos page.
5. Complete the test with a conclusion stated in the context.
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