1 are there any important and significant differences...

Name: 1 are there any important and significant differences between men and women in how they feel about eating fast food q14 1 7 what does this mean for marketers of fast food 2 what is the assoc 18715
Uploaded: 2022-08-28T11:44:37-08:00
Duration: 7 min 24 s
Channel: Paul A.
Description: 1 are there any important and significant differences between men and women in how they feel about eating fast food q14 1 7 what does this mean for marketers of fast food 2 what is the assoc 18715

1. Are there any important and significant differences between men and women in how they feel about eating fast food (Q14 1-7)? What does this mean for marketers of fast food? 2. What is the association between the frequency of eating in fast food restaurants and how someone describes how they feel about eating fast food (Q14 1-7: in this case treat these ordinal measures as a scale variable). What would be your marketing recommendations?3. Using the largest association in Q4 above, build a forecast model that predicts the frequency of eating at fast food restaurants. What is the Coefficient of Determination? What does its value mean? What is the intercept and slope coefficient and what does each mean in this model? 4. Is having younger children in the home a predictor of buying fast food more often? Use the last variable in the data set (Recoded Usage of Fast Food) and rank the Chi-Square P-Values of d3a-2, d3a-3, and d3a-4. What does this data mean, and what would be your marketing recommendation?

Transcript

00:01 Once again, welcome to a new problem.

00:05 This time we're dealing with hypothesis testing.

00:09 We're dealing with hypothesis testing.

00:11 And whenever you think about hypothesis testing, there are options for one -tailed tests.

00:23 And when you look at one -tailed tests, there are two options.

00:27 The first option is right -tailed.

00:31 So we have a right -tail test.

00:34 And then the second option is a left -tailed test.

00:40 And the right -tail test, this means that in terms of your normal distribution, you're testing the right side of the distribution.

00:50 And then the left tail, you're testing the left side of the distribution.

00:54 We also have a two -tailed test, so a two -tail test such that we can test both sides of the distribution for the two -tail test, and the test requirements include the now hypothesis.

01:14 So when we're testing, we have the now hypothesis, and we also have the alternative hypothesis.

01:22 So these are the tests, different types of tests that were running.

01:30 We're looking at a new problem and in this particular problem, we have a market research company, and so in this market research company we have a selection of 60 participants, so we're looking at 60 participants and the goal is to rate the two types of advertisements on a scale of 1 to 100.

02:03 And so the first question we're looking at is both odds equally effective.

02:10 So we're going to write, we want to write the now and alternative hypotheses.

02:15 Remember, these are ratings.

02:17 So in number one, we're going to say that the now is that the average ratings for the two advertisement add one and add two equivalent.

02:32 And then the alternative hypothesis is that the two ads are not equal.

02:39 So they're different.

02:40 The test statistic is to test for these differences.

02:46 So we use a t test such that we're saying the two means sigma x1 and sigma x2.

02:57 These two will end up to zero.

03:01 And then we have the standard error assuming the variances are different.

03:07 So if we assume different variances, this is going to be the standard error.

03:12 And then the second part of the problem is that.

03:16 Now we have 55 customers, so we have 55 customers in a store, and they're going to fill in a survey...

Question

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