Business Maths Statistics Assignment 1

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BMS11 Business Maths and Statistics ASSIGNMENT 1 DESCRIPTIVE STATISTICS USING EXCEL PART B. QA). The pie charts show that a higher percentage of the male gender has tried the product in comparison to the female gender. Over 50% of both genders have tried the product. However, the fact that the percentage of males who tried the product is higher, suggests that gender does play a role in whether the people will try the product. Yet the role genders play is small, because the difference between the percentage of females who tried the product and males who tried the product is small at only 7%. However, since the graphs do not compare the genders within the total sample surveyed and are only a percentage of each specific gender, more…show more content…
The type of data itself is nominal not numerical. The income of both males and females is not as accurate as we would like, because it has been collected within large income ranges, for example $0 to $25,000. Therefore to use the data, midpoints must be found, doing this has caused the data to become very general and does not show specifics on income levels per person. The incomes are shown on the graph as midpoints which have a large range within them. This further shows that the information is too general for many business applications and decision making. The graph has narrowed down the five income midpoints of interest to three. These three income midpoints were $12,500 $37,500 & $62,500. However exactly what income levels within these ranges have not been determined. This means that the information is vague. The information would be more useful if specific income levels and ‘have tried’ frequencies per income were investigated. The graph would be more useful if it showed actual income levels and numbers of people within that income level who had tried the product. It only tells us the midpoint which has a large range and therefore, the information is quite general. This information would be fine if we wanted to target general income groups but it would be insufficient if we wanted to determine specific income levels who have tried the product, as we do not know what that income level
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