This is linear regression 3 solving in RStudio

Coefficients:

Estimate Std. Error t value Pr(>|t|)

(Intercept)10.64494990.864289612.316< 2e-16 ***

genre_action_i-1.14793050.5309396-2.1620.0314 *

genre_simulation_i2.76989180.63777224.343 1.93e-05 ***

dev_rating1.33971410.30740804.358 1.81e-05 ***

num_streams-0.00483100.0006958-6.943 2.44e-11 ***

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Signif. codes:0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 4.045 on 295 degrees of freedom

Multiple R-squared:0.2341, Adjusted R-squared:0.2237

F-statistic: 22.55 on 4 and 295 DF,p-value: 2.905e-16

The question is

how can you interpret the results of the model? [Select all that apply]

A)The adjusted R squared is [0.22, 0.23]

B)The probability that such a model is better at explaining the variation in payments by chance alone is less than 0.001

C)Except for the number of streams variable, there is no evidence that other variables have a causal effect on payments

D)Except for the developer rating variable, there is no evidence that other variables have a causal effect on payments