5-4 Quiz Python Functions

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Southern New Hampshire University *

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Mathematics

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Feb 20, 2024

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5-4 Quiz: Python Functions Your work has been saved and submitted Written Feb 4, 2024 8:42 AM - Feb 4, 2024 8:47 AMAttempt 1 of 2 You have successfully submitted the Module Five quiz. Please review the learning resources or reach out to your instructor with any questions. Attempt Score 15 / 15 - A Overall Grade (Highest Attempt) 15 / 15 - A Question 1 3 / 3 points The ols() method in statsmodels was used to fit a simple linear regression model using “Exam4” as the response variable and “Exam1” as the predictor variable. The output is shown below. A text version is available . What is the correct regression equation based on this output? Is this model statistically significant at 5% level of significance (alpha = 0.05)? Select one. (Hint: Review results of F-statistic) Question options: , model is statistically significant , model is not statistically significant , model is not statistically significant
, model is statistically significant Question 2 3 / 3 points Which of the following Python methods return the correlation coefficient? Select all that apply. Question options: pearsonr method from scipy.stats submodule corr method from pandas dataframe Question 3 3 / 3 points The ols() method in statsmodels is used to fit a simple linear regression model using “Exam4” as the response variable and “Exam3” as the predictor variable. The output is shown below. A text version is available . What is the correct regression equation based on this output? Is this model statistically significant at 10% level of significance (alpha = 0.10)? Select one. (Hint: Review results of F-statistic) Question options: Exam4 = 76.85 + 0.206 Exam3, model is not statistically significant Exam4 = 68.9576 + 0.1028 Exam3, model is not statistically significant Exam4 = 76.85 + 0.206 Exam3, model is statistically significant Exam4 = 68.9576 + 0.1028 Exam3, model is statistically significant Question 4 3 / 3 points The height and grade point average of 50 randomly selected students are recorded. The following Python code is used to fit a simple linear regression model using data collected from the sample
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