Answer: Explanatory variable = " number of times the owner has an advertisement played on the radio"
Response variable = "number of new customers who will visit a shop"
Step-by-step explanation:
- An explanatory variable is a kind of independent variable that can be manipulated by researcher in a study to check the response of the response variable.
In the given situation , the business owner is predicting the number of new customers who will visit a shop based on the number of times the owner has an advertisement played on the radio.
Here , He is controlling the advertisement played on the radio to see the response of customers.
Therefore ,
Explanatory variable = " number of times the owner has an advertisement played on the radio"
Response variable = "number of new customers who will visit a shop"
Answer:
-1/8
Step-by-step explanation:
Answer:
(-2,2)
Step-by-step explanation:
hope this helps :)
- For this study, we should use t-test and the null and alternative hypotheses would be given by H₀: μ = 7 and H₁: μ < 7.
- The test statistic is -1.941 and the p-value (0.0381) is <u>greater than</u> α = 0.01.
- Based on this, we should <u>fail to reject</u> the null hypothesis.
- Thus, the final conclusion is that the data suggest the population mean is not significantly lower than 7 at α = 0.01, so there is statistically insignificant evidence to conclude that the population mean waiting time to be admitted into the hospital from the emergency room for patients at rural hospitals is equal to 7 hours.
<h3>What is a null hypothesis?</h3>
A null hypothesis (H₀) can be defined the opposite of an alternate hypothesis (H₁) and it asserts that two (2) possibilities are the same.
<h3>How to calculate value of the test statistic?</h3>
The test statistics can be calculated by using this formula:

<u>Where:</u>
- is the standard deviation.
- n is the number of hours.
For this study, we should use t-test and the null and alternative hypotheses would be given by:
H₀: μ = 7
H₁: μ < 7

t = -0.7/0.3606
t = -1.941.
For the p-value, we have:
P-value = P(t < -1.9412)
P-value = 0.0381.
Therefore, the p-value (0.0381) is <u>greater than</u> α = 0.01. Based on this, we should <u>fail to reject</u> the null hypothesis.
Thus, the final conclusion is that the data suggest the population mean is not significantly lower than 7 at α = 0.01, so there is statistically insignificant evidence to conclude that the population mean waiting time to be admitted into the hospital from the emergency room for patients at rural hospitals is equal to 7 hours.
Read more on null hypothesis here: brainly.com/question/14913351
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The calculations come out to be <span>2003.44921875, so there would be 2003 subscribers in 1990</span>