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The “last name” effect in purchasing. The Journal of Consumer Research (August 2011) published a study demonstrating the “last name” effect—i.e., the tendency for consumers with last names that begin with a later letter of the alphabet to purchase an item before consumers with last names that begin with earlier letters. To facilitate the analysis, the researchers assigned a number, x, to each consumer based on the first letter of the consumer’s last name. For example, last names beginning with “A” were assigned x = 1; last names beginning with “B” were assigned x = 2; and last names beginning with “Z” were assigned x = 26.

a. If the first letters of consumers’ last names are equally likely, find the probability distribution for x.

b. Find E (x) using the probability distribution, part a. If possible, give a practical interpretation of this value.?

c. Do you believe the probability distribution, part a, is realistic? Explain. How might you go about estimating the true probability distribution for x

Short Answer

Expert verified
  1. The probability distribution of x is f(x)=1n where x = 1,...26
  2. Ex=a+b2and the interpretation of the value isEx=1+262=13.5
  1. The probability distribution is realistic. Estimating the probability distribution of x isfx=1n

where x = 1,...26.

Step by step solution

01

Given information

Given that researchers assigned a number is x. Here the “last name” effect in purchasing.

02

Finding the probability distribution for x

a.

The first letters of consumers last names are equally likely. There are equally likely so there follows discrete uniform distribution. Then the probability distribution for x is

f(x)=1n where x = 1,...26

03

Finding E(x) and also define the practical interpretation

b.

The mean value using this distribution to given by

Ex=a+b2

The practical interpretation is- Here researchers assigned by numbers. So then the probability distribution of the value is

Ex=1+262=13.5

04

Probability distribution is realistic and estimating the true probability distribution

c.

Yes the probability distribution is realistic.

The true probability distribution foris defined by discrete uniform distribution. We can also calculate this in step-2.

Thus, the step-2 follows the distribution that will be given by fx=1nwhere x = 1,...26.

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Most popular questions from this chapter

Assume that σ12222. Calculate the pooled estimator σ2 for each of the following cases:

a.s12=120,s22=100,n1=n2=25

b.s12=12,s22=20,n1=20,n2=10

c.s12=.15,s22=.20,n1=6,n2=10

d.s12=3000,s22=2500,n1=16,n2=17

Note that the pooled estimate is a weighted average of the sample variances. To which of the variances does the pooled estimate fall nearer in each of the above cases?

A random sample of size n = 121 yielded p^ = .88.

a. Is the sample size large enough to use the methods of this section to construct a confidence interval for p? Explain.

b. Construct a 90% confidence interval for p.

c. What assumption is necessary to ensure the validity of this confidence interval?

Question: Refer to the Bulletin of Marine Science (April 2010) study of lobster trap placement, Exercise 6.29 (p. 348). Recall that the variable of interest was the average distance separating traps—called trap-spacing—deployed by teams of fishermen. The trap-spacing measurements (in meters) for a sample of seven teams from the Bahia Tortugas (BT) fishing cooperative are repeated in the table. In addition, trap-spacing measurements for eight teams from the Punta Abreojos (PA) fishing cooperative are listed. For this problem, we are interested in comparing the mean trap-spacing measurements of the two fishing cooperatives.

BT Cooperative

93

99

105

94

82

70

86

PA Cooperative

118

94

106

72

90

66

98


Source: Based on G. G. Chester, “Explaining Catch Variation Among Baja California Lobster Fishers Through Spatial Analysis of Trap-Placement Decisions,” Bulletin of Marine Science, Vol. 86, No. 2, April 2010 (Table 1).

a. Identify the target parameter for this study.b. Compute a point estimate of the target parameter.c. What is the problem with using the normal (z) statistic to find a confidence interval for the target parameter?d. Find aconfidence interval for the target parameter.e. Use the interval, part d, to make a statement about the difference in mean trap-spacing measurements of the two fishing cooperatives.f. What conditions must be satisfied for the inference, part e, to be valid?

Suppose you want to estimate the difference between two population means correct to within 1.8 with a 95% confidence interval. If prior information suggests that the population variances are approximately equal to σ12=σ22=14 and you want to select independent random samples of equal size from the populations, how large should the sample sizes n1, and n2, be?

The “winner’s curse” in transaction bidding. In transaction bidding, the “winner’s curse” is the miracle of the winning (or loftiest) shot price being above the anticipated value of the item being auctioned. The Review of Economics and Statistics (Aug. 2001) published a study on whether shot experience impacts the liability of the winner’s curse being. Two groups of a stab in a sealed-shot transaction were compared (1)super-experienced stab and (2) less educated stab. In the super-experienced group, 29 of 189 winning flings were above the item’s anticipated value; 32 of 149 winning flings were above the item’s anticipated value in the less-educated group.

  1. Find an estimate of p1, the true proportion of super educated stab who fell prey to the winner’s curse
  2. Find an estimate of p2, the true proportion of less-educated stab who fell prey to the winner’s curse.
  3. Construct a 90 confidence interval for p1-p2.
  4. d. Give a practical interpretation of the confidence interval, part c. Make a statement about whether shot experience impacts the liability of the winner’s curse being.
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