Suppose You've Run a Regression Relating Revenues to TV Ads

question 18

Multiple Choice

Suppose you've run a regression relating Revenues to TV Ads and Online Ads. You are willing to make the necessary assumptions to deduce causality and run hypothesis tests. Your results are as follows: $$\begin{array} { | l | c | c | c | c | } \hline & \text { Coefficients } & \text { Stardard Error } & \text { t-Stat } & \text { P-value } \\\hline \text { Iratercept } & 5988.043107 & 2202.136765 & 2.719196738 & 0.006881952 \\\hline \text { IV Ads } & 199.6320212 & 27.82658673 & 7.174146912 & 4.63154 \mathrm { E } - 12 \\\hline \text { Orline Ads } & 53.52092429 & 41.0818115 & 1.302788809 & 0.193533758 \\\hline\end{array}$$ If you tested the null hypothesis that Online Ads have no impact on Revenues at the 90% confidence level (i.e., 90% degree of support) , you would:

• A) Reject, and conclude Online Ads do impact Revenues
• B) Fail to reject, and conclude Online Ads do impact Revenues
• C) Fail to reject, and conclude there is insufficient evidence to establish that Online Ads impact Revenues
• D) None of the answers is correct

---

Definitions:

Quality And Value

Refers to the assessment of a product's or service's overall excellence and worth, combining its inherent characteristics and the benefits it provides to the consumer.

Store Influences

Factors within a retail environment that affect consumer behavior, such as layout, design, and ambiance.

Impulse Item

Products that are typically bought without prior planning or consideration, often as a result of spontaneous desire.

Customer Complaints

Refers to expressions of dissatisfaction or concerns raised by customers regarding a company's products or services.