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 8 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) 1 310 204 106 2 982 903 79 3 861 921 -60 4 640 413 227 5 656 599 57 6 802 675 127 7 924 648 276 8 913 789 124 Table 1 Based on these data, can the owner conclude, at the 0.01 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 0.01 level of significance:(Round to at least three decimal places.) and At the 0.01 level, can the owner conclude that the mean daily sales of the two stores differ? Yes No
Contingency Table
A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.
Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
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.
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| Table 1 |
Based on these data, can the owner conclude, at the
level of significance, that the mean daily sales of the two stores differ? Answer this question by performing a hypothesis test regarding
(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
Perform a two-tailed test.
| The null hypothesis: |
H0:
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| The alternative hypothesis: |
H1:
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| The type of test statistic: | (Choose one)ZtChi squareF | |||
| The value of the test statistic: (Round to at least three decimal places.) |
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| The two critical values at the
0.01
(Round to at least three decimal places.) |
and
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| At the 0.01 level, can the owner conclude that the mean daily sales of the two stores differ? |
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