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Statistics can effect the product's marketing strategy tremendously by helping marketers and decision makers to make informed decisions.
Hypothesis Testing is when you formulate H0 and H1. You then select appropriate test and choose level of significance. You then can calculate the test statistic and determine the probability associated with the test statistic. You then determine the critical value of the test statistic . You compare the level of significance, α and determine if TScr falls into the non rejecting region. You then reject or not reject the null hypothesis and draw marketing research conclusion. The null hypothesis is a statement of the status quo, one of no difference or no effect. If the null hypothesis is not rejected, then no changes will be made. If an alternative hypothesis is one in which some difference or effect is expected. The null hypothesis may be rejected , but it can never be accepted based on a single test. In the marketing research, the null hypothesis is formulated in such a way that its rejection leads to the acceptance of the desired conclusion. For example, take one marketing test in which a new Internet Shopping Service will be introduced if more than 40% of people use it: To formulate the test:
H0 : u <= .40
HA: u > .40
The required data are collected and the value of the test statistic computed.
In our example, 30 people were surveyed and 17 shopped on the internet. The value of the sample proportion is p = 17/30 = 0.567
The value of Ϭ is 0.089
Using the test statistics z, we calculated the z score:
Z cal = p – u/ Ϭp
= 0.567 -.040/ 0.089
We used the z-table under normal idiPlease let me know if you need any clarification. I'm always happy to answer your questions.
We used the z-table under normal distribution to find the p-value. We use the critical value of α = 0.05
If the p-value is less than 0.05, then we reject the null hypothesis. Since the p-value is .0301, then we reject the null hypothesis. The rule is that if the probability associated with the calculated value of the test statistic ( Z cal) is less than the level of significance (α), the null hypothesis is rejected. In our case, the p-value is 0.0301. This is less than the level of significance of α = 0.05. Thus, the null hypothesis is rejected. If the calculated value of the test statistic is greater than the critical value of the test statistic, the null hypothesis is rejected.
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