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) 1 927 759 168 2 327 312 15 3 872 645 227 4 330 332 -2 5 684 711 -27 6 625 471 154 7 436 557 -121 8 615 694 -79 9 674 632 42 10 975 1013 -38 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. The null hypothesis: H0: The alternative hypothesis: H1: The type of test statistic: (Choose one)ZtChi squareF 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

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

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	927	759	168
2	327	312	15
3	872	645	227
4	330	332	-2
5	684	711	-27
6	625	471	154
7	436	557	-121
8	615	694	-79
9	674	632	42
10	975	1013	-38

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

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.


The null hypothesis:	H0:
The alternative hypothesis:	H1:
The type of test statistic:	(Choose one)ZtChi squareF

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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