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In 2022, a charity had organised 87 events throughout the year to raise funds for local causes. Most of the events were hosted online but more in-person events were organised in the latter half of the year. The charity want to investigate the relationship between the funds raised (in GBP£ after costs) and the event type (online or in-person) with respect to the number of people who attended the event. The charity's event manager has collected the data from the year and has fitted a linear regression model R. Write a short report based on the R output present on the next page. You report should contain an explanation of the model that the charity's event manager has fitted (be clear with your notation), provide appropriate advice on the relationship between funds raised and event type, and comment on the quality of the fitted regression model.

In 2022, a charity had organised 87 events throughout the year to raise funds for local causes. Most of the events were hosted online but more in-person events were organised in the latter half of the year. The charity want to investigate the relationship between the funds raised (in GBP£ after costs) and the event type (online or in-person) with respect to the number of people who attended the event. The charity's event manager has collected the data from the year and has fitted a linear regression model R. Write a short report based on the R output present on the next page. You report should contain an explanation of the model that the charity's event manager has fitted (be clear with your notation), provide appropriate advice on the relationship between funds raised and event type, and comment on the quality of the fitted regression model.

MATLAB: An Introduction with Applications
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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The first image is question and the second one is R output.

In 2022, a charity had organised 87 events throughout the year to raise funds for local causes. Most of the events were hosted online but more in-person events were organised in the latter half of the year. The charity want to investigate the relationship between the funds raised (in GBP£ after costs) and the event type (online or in-person) with respect to the number of people who attended the event. The charity's event manager has collected the data from the year and has fitted a linear regression model R. Write a short report based on the R output present on the next page. You report should contain an explanation of the model that the charity's event manager has fitted (be clear with your notation), provide appropriate advice on the relationship between funds raised and event type, and comment on the quality of the fitted regression model.
Transcribed Image Text:In 2022, a charity had organised 87 events throughout the year to raise funds for local causes. Most of the events were hosted online but more in-person events were organised in the latter half of the year. The charity want to investigate the relationship between the funds raised (in GBP£ after costs) and the event type (online or in-person) with respect to the number of people who attended the event. The charity's event manager has collected the data from the year and has fitted a linear regression model R. Write a short report based on the R output present on the next page. You report should contain an explanation of the model that the charity's event manager has fitted (be clear with your notation), provide appropriate advice on the relationship between funds raised and event type, and comment on the quality of the fitted regression model.
Call: 1m (formula = funds_raised Residuals: Min 1Q Median 3Q Max -6685.2 -1959.5 -354.1 1790.3 10079.7 Coefficients: (Intercept) Estimate Std. Error t value Pr(>|t|) -6295.3046 1253.6679 -5.022 2.89e-06 *** num_people 0.1008 20.192 < 2e-16 *** event_typeOnline 1266.0849 770.0063 1.644 2.0358 0.104 Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05.¹0.11 Residual standard error: 3069 on 83 degrees of freedom Multiple R-squared: 0.8745, Adjusted R-squared: 0.8715 F-statistic: 289.2 on 2 and 83 DF, p-value: < 2.2e-16 Residuals Standardized residuals -5000 0 5000 ετι 5000 10000 Residuals vs Fitted -2 O 00 O 000000 -1 1936 20000 Fitted values 60 Normal Q-Q T 0 e num_people + event_type, data = charity_data) 30000 1 Theoretical Quantiles 00⁰000 2 40000 60 VIStandardized residualsl 0.5 1.0 1.5 0.0 40000 Funds Raised (£) 25000 10000 oo 5000 10000 Event Type o In Person x Online ⁰0⁰ ∞ T Scale-Location O 6900 10000 01.836 ooo O 00 20000 Fitted values 60 O Data Scatterplot 15000 80 T 30000 00 Number of People at Event O O O 20000 O 40000
Transcribed Image Text:Call: 1m (formula = funds_raised Residuals: Min 1Q Median 3Q Max -6685.2 -1959.5 -354.1 1790.3 10079.7 Coefficients: (Intercept) Estimate Std. Error t value Pr(>|t|) -6295.3046 1253.6679 -5.022 2.89e-06 *** num_people 0.1008 20.192 < 2e-16 *** event_typeOnline 1266.0849 770.0063 1.644 2.0358 0.104 Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05.¹0.11 Residual standard error: 3069 on 83 degrees of freedom Multiple R-squared: 0.8745, Adjusted R-squared: 0.8715 F-statistic: 289.2 on 2 and 83 DF, p-value: < 2.2e-16 Residuals Standardized residuals -5000 0 5000 ετι 5000 10000 Residuals vs Fitted -2 O 00 O 000000 -1 1936 20000 Fitted values 60 Normal Q-Q T 0 e num_people + event_type, data = charity_data) 30000 1 Theoretical Quantiles 00⁰000 2 40000 60 VIStandardized residualsl 0.5 1.0 1.5 0.0 40000 Funds Raised (£) 25000 10000 oo 5000 10000 Event Type o In Person x Online ⁰0⁰ ∞ T Scale-Location O 6900 10000 01.836 ooo O 00 20000 Fitted values 60 O Data Scatterplot 15000 80 T 30000 00 Number of People at Event O O O 20000 O 40000
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