The owner of a chain of mini-markets wants to compare the sales performance of two of her stores, Store 1 and Store 2. Sales can vary considerably depending on the day of the week and the season of the year, so she decides to eliminate such effects by making sure to record each store's sales on the same sample of days. After choosing a random sample of 10 days, she records the sales (in dollars) for each store on these days, as shown in Table 1. Day Store 1 Store 2 Difference (Store 1 - Store 2) 1 760 791 -31 2 856 571 285 3 516 443 73 4 768 646 122 5 375 427 -52 6 312 210 102 7 231 15 216 8 779 602 177 9 633 297 336 10 690 601 89 Table 1 Based on these data, can the owner conclude, at the 0.10 level of significance, that the mean daily sales of the two stores differ? Answer this question by performing a hypothesis test regarding μd (which is μ with a letter "d" subscript), the population mean daily sales difference between the two stores. Assume that this population of differences (Store 1 minus Store 2) is normally distributed. Perform a two-tailed test. Then fill in the table below. Carry your intermediate computations to at least three decimal places and round your answers as specified in the table. The null hypothesis: H0: The alternative hypothesis: H1: The type of test statistic: (Choose one) Z t Chi square F The value of the test statistic: (Round to at least three decimal places.)

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.6: Summarizing Categorical Data

Problem 10CYU

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The owner of a chain of mini-markets wants to compare the sales performance of two of her stores, Store 1 and Store 2. Sales can vary considerably depending on the day of the week and the season of the year, so she decides to eliminate such effects by making sure to record each store's sales on the same sample of days. After choosing a random sample of 10 days, she records the sales (in dollars) for each store on these days, as shown in Table 1.

Day	Store 1	Store 2	Difference (Store 1 - Store 2)
1	760	791	-31
2	856	571	285
3	516	443	73
4	768	646	122
5	375	427	-52
6	312	210	102
7	231	15	216
8	779	602	177
9	633	297	336
10	690	601	89

Table 1

Based on these data, can the owner conclude, at the 0.10 level of significance, that the mean daily sales of the two stores differ? Answer this question by performing a hypothesis test regarding μd (which is μ with a letter "d" subscript), the population mean daily sales difference between the two stores. Assume that this population of differences (Store 1 minus Store 2) is normally distributed.

Perform a two-tailed test. Then fill in the table below. Carry your intermediate computations to at least three decimal places and round your answers as specified in the table.

The null hypothesis:	H0:
The alternative hypothesis:	H1:
The type of test statistic:	(Choose one) Z t Chi square F

The value of the test statistic: (Round to at least three decimal places.)
The two critical values at the 0.10 level of significance: (Round to at least three decimal places.)	and
At the 0.10 level, can the owner conclude that the mean daily sales of the two stores differ?	Yes	No

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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