import pandas as pd

Load the uploaded Excel file to examine its contents

file_path = '/mnt/data/1732366448656m655f9u2.xlsx' excel_data = pd.ExcelFile(file_path)

Display sheet names to understand the structure of the file

excel_data.sheet_names['Sheet1']['Sheet1']success# Load the data from the first sheet to inspect its content data = excel_data.parse('Sheet1')

Display the first few rows of the data to understand its structure

data.head() Month Advertising Spend (in $1,000s) Monthly Revenue (in $1,000s) 0 1 10000 50000 1 2 15000 55000 2 3 12000 54000 3 4 20000 65000 4 5 25000 70000 Month Advertising Spend (in $1,000s) Monthly Revenue (in $1,000s) 0 1 10000 50000 1 2 15000 55000 2 3 12000 54000 3 4 20000 65000 4 5 25000 70000successThe dataset appears to contain information about months, advertising spend, and monthly revenue. To determine the p-value for testing if the slope coefficient, $B_1$, differs from zero, I'll perform a linear regression analysis. Let me compute the p-value.import statsmodels.api as sm

Extract the independent (X) and dependent (Y) variables for regression

X = data['Advertising Spend (in $1,000s)'] Y = data['Monthly Revenue (in $1,000s)']

Add a constant term to the independent variable for the regression model

X = sm.add_constant(X)

Fit the linear regression model

model = sm.OLS(Y, X).fit()

Extract the p-value for the slope coefficient (B1)

p_value = model.pvalues['Advertising Spend (in $1,000s)'] p_value_rounded = round(p_value, 3)

p_value_rounded0.00.0successThe p-value for testing whether the slope coefficient ($B_1$) differs from zero is $0.000$, rounded to three decimal places. This indicates strong evidence against the null hypothesis that the slope is zero.

Would you like further details on the analysis or interpretation of this result? Here are 5 related questions to explore:

1. What does a p-value of $0.000$ imply in the context of this dataset?
2. Can you provide the full regression summary for additional insights?
3. How does the advertising spend correlate with monthly revenue based on the slope?
4. What are the assumptions of the regression model used here?
5. How can this result be applied in business decision-making?

Tip: Always check the confidence intervals for slope coefficients to understand the range of plausible values for your estimate.