is often useful for retailers to determine why their potential customers chose to visit their store. Possible reasons include advertising, advice from a friend, or previous experience. To determine the effect of full-page advertisements in the local newspaper, the owner of an electronic-equipment store asked randomly selected people who visited the store whether they had seen the ad. He also determined whether the customers had bought anything, and if so, how much they spent. Among the respondents who saw the ad, 49 made an average purchase of $97.38 with a variance of $622. Among the respondents who did not see the ad, 21 made an average purchase of $92.01 with a variance of $283.3. Can the owner conclude that customers who see the ad spend more than those who do not see the ad (among those who make a purchase) at 5% significance level?
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
It is often useful for retailers to determine why their potential customers chose to visit their store. Possible reasons include advertising, advice from a friend, or previous experience. To determine the effect of full-page advertisements in the local newspaper, the owner of an electronic-equipment store asked randomly selected people who visited the store whether they had seen the ad. He also determined whether the customers had bought anything, and if so, how much they spent. Among the respondents who saw the ad, 49 made an average purchase of $97.38 with a variance of $622. Among the respondents who did not see the ad, 21 made an average purchase of $92.01 with a variance of $283.3.
Can the owner conclude that customers who see the ad spend more than those who do not see the ad (among those who make a purchase) at 5% significance level?
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Population:
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Formula #: Answer |
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Hypothesis |
Null H0 : (μ, π, σ², μd, μ1 - μ2, π1- π2, σ₁² / σ₂²) Alternate HA: (μ, π, σ², μd, μ1 - μ2, π1- π2, σ₁² / σ₂²) |
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Decision Criteria |
α = Graph: 2-tailedRight tailedLeft Tailed Distribution: Z, t, χ2 or F (if applicable) Left Critical Value: Answer (if applicable) Right Critical Value: Answer |
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Calculated Value |
Z-Calculated, t-Calculated, χ2-Calculated or F-Calculated and the answer? |
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Conclusion |
Do NOT Reject Null, Reject Null or Neither possible |
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| Conclusion-2 | There is (?) evidence to infer that customers who see the ad and make a purchase spend more than those who do not see the ad and make a purchase. |
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