Texts frustrated at age 30 like many of his generation bob...

Texts: FRUSTRATED AT AGE 30 Like many of his generation, Bob is mired in debt. He owes $23,000 on his college. The fact that the go-go years of the late-1990s are history has set in. The rules have changed. And we Generation Xers are getting hit hard. We had to go through a hiring bonus on my first job. The competition by employers for good people drove salaries up. The good news was, when we graduated, the job market was great. I got a $5,000 job in six months. The same company for over 20 years. But my dad has job security. And he has a nice salary. When I was 28, I was making more money than my dad, who had been with the same company for over 20 years. QUESTIONS 1. Analyze Bob using the Maslow need hierarchy. 2. Analyze Bob's lack of motivation using organizational justice and expectancy theory. 3. If you were Bob's boss, what could you do to positively influence his motivation? 4. What are the implications of this case for employers hiring Generation Xers?

Transcript

00:01 Hello and welcome back to statistics.

00:04 Today we have a statistical test that we need to conduct.

00:08 So we need to find if there is convincing evidence that the proportion of gen xers who do not pay off their credit cards each month is greater than this proportion for millennials.

00:18 And so we need to test this hypothesis using a significance level of 0 .05.

00:23 So we know that our alpha is going to be 0 .05.

00:30 All right.

00:30 So let's just write down all the information that we can know and just go through the information in the paragraph.

00:38 A company surveyed adult americans about their consumer debt.

00:42 They reported that 48 % of millennials and 59 % of gen xers did not pay off their credit cards each month and therefore carried a balance from month to month.

00:53 So for gen x and then millennials are p.

01:00 So p1 for gen x will be .59.

01:07 And p2, four millennials, will be .48.

01:14 And suppose that these percentages were based on representative samples of 450 millennials and 300 gen xers.

01:21 So n2 will be 400 millennials and n1 will be 300 gen xers.

01:29 And now is there convincing evidence that the proportion of gen xers? xers, we do not pay off their credit card each month, is greater than this proportion for millennials.

01:39 So, let's just get right into this test.

01:42 The first step of any hypothesis test is our, of course, stating our null and alternative hypotheses.

01:49 So our null hypothesis, or h not, that is going to be basically what we can assume.

01:58 So in this case, since it's asking if that the proportion of gen xers is great, if it is greater than the proportion for millennials.

02:10 So we can assume the opposite that the proportion of gen xers is actually equal to the proportion of millennials because you always start the null hypothesis with an equality and then the alternative hypothesis with an inequality.

02:28 So in this case, p1 would be equal to p2 or in terms of how the problem has the answers, p1 minus p2 is equal to zero.

02:41 Now for the alternative hypothesis, we're looking for p1, gen xers, is greater than p2 millennials.

02:50 So p1 greater than p2, i .e., p1 minus p2, is greater than zero.

02:58 So the difference would be greater than zero.

03:01 So what this looks like, so we're looking for significant, level of 0 .05.

03:10 So this right here will be our rejection region and everything left, so that z value will be 0 .95, which anything to the left of that would just be due to random chance of this specific proportion.

03:26 So in this case, our gen xers are going to be the sample statistics.

03:33 So p1 will actually be p hat.

03:35 P hat is equal to p1 because we're assuming the population is the millennials because of our null hypothesis so that like p1 the proportion of gen x is equal to p2 which is the proportion of millennial so p is going to be p2 and so to find a test statistic before which i'm so sorry i cannot speak today so the next step is going to be to find a test statistic and because of the central limit theorem, i have the formula to find it in the top right here in blue.

04:14 Z is equal to p hat minus p over the square root of p hat times one minus p hat over n.

04:21 So that's going to be how we find our test statistic and then our p value...

Question

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