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# Use Common Statistical Tests to Draw Conclusions From Data (Example)

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Use Common Statistical Tests to Draw Conclusions from Data Name: Institution: Abstract In the course of their day-to-day jobs managers are expected to make a number of decisions for their organizations. Some of the decisions have far-reaching ramifications and the managers need to take extra precautions. It is common for managers to get data from various sources when faced with the need to make decisions. While raw numbers can be appealing to the eyes it is important to carry out some statistical tests to make well-informed conclusions. One of the tests usually performed on a set of data is the chi-square test. The Chi-square test is intended to test how likely it is that an observed distribution is due to chance. had an effect on the value of sales recorded. Software used Observed-O Expected-E (O-E) (O-E)^2 (O-E)^2/E Northeast 165 150 15 225 1.5000 Southeast 200 150 50 2500 16.6667 Central 175 150 25 625 4.1667 West 180 150 30 900 6.0000 Total         28.3333             software not used           Northeast 100 150 -50 2500 16.6667 Southeast 125 150 -25 625 4.1667 Central 125 150 -25 625 4.1667 West 130 150 -20 400 2.6667 Total         27.6667 Based on the tests carried the Vice President can now confidently roll out the use of the software. Reference Bozeman Science. (2011 November 13). Chi-squared test [Video file]. Retrieved from https://www.youtube.com/watch?v=WXPBoFDqNVk [...]

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Company W is testing a sales software. Its sales force of 500 people is divided into four regions: Northeast, Southeast, Central, and West. Each salesperson is expected to sell the same amount of products. During the last 3 months, only half of the sales representatives in each region were given the software program to help them manage their contacts. The Northeast using the software sold 165 and the group with no software sold 100, The Southeast with software sold 200 and the group with no software sold 125. The Central groups with software sold 175 and the group with no software sold 125. The West group with software sold 180 and the group with no software sold 130. Using this data calculate the Chi Square statistic. The VP of Sales at WidgeCorp, who is comfortable with statistics, wants to know the possible null and alternative hypotheses for a nonparametric test on this data using the chi-square distribution. A nonparametric test is used on data that are qualitative or categorical, such as gender, age group, region, and color. It is used when it does not make sense to look at the mean of such variables. (You can refer to the article for this phase for further information.) The following information may be helpful in understanding Chi Square and Hypothesis testing: Chi Square / Hypothesis Testing Please review this helpful video. The presenter uses the "flip of the coin" and the "role of the die." These are examples and analogies used in the CTU resources. The following are assumptions you might make in this assignment that might make the assignment more helpful and make the responses more uniform: Continue to use the Widgecorp context. Assume the salespersons are test sales of snack foods or drinks. Additionally, assume you have the same number of salespersons in each region. Reference Bozeman Science. (2011, November 13). Chi-squared test [Video file]. Retrieved from https://www.youtube.com/watch?v=WXPBoFDqNVk

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Words 550

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06.09.2017

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