Group Assignment – Statistics

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Running head:GROUP ASSIGNMENT – STATISTICSGroup Assignment – StatisticsNameCourse NumberDateFaculty Name
GROUP ASSIGNMENT – STATISTICS2Group Assignment – Statistics1.Frequency distribution and histograma)A table of frequency distribution, relative frequency distribution and percent frequencydistribution with a width of $50Table1: A table of Frequency distribution, relative frequency distribution and percent frequencydistributionWidthFrequencyRelativeFrequencyCumulative RelativeFrequencyPercentCumulativepercent15030.060.066.00%6.00%200150.30.3630.00%36.00%250140.280.6428.00%64.00%30060.120.7612.00%76.00%35040.080.848.00%84.00%40030.060.96.00%90.00%45030.060.966.00%96.00%50020.0414.00%100.00%More0010.00%100.00%According to the frequency table above, most of the shipping charges are below 250 dollarsper furniture order. Based on the cumulative percentage column, more than 50% of the shippingcharges selected are below that threshold. Prices between 150 and 200 have the highestfrequency of 30% followed by prices between 200 and 250 with 28% then prices between 250and 300 which takes 12%. Cumulatively, 70% of the furniture shipping charges selected atrandom are between 150 and 300. The width between 450 and 500 has the least frequency of 2price values which accounts for 4%(Siegel, 2012).b)A histogram of Shipping Charges which shows the percent frequency distribution
GROUP ASSIGNMENT – STATISTICS3150200250300350400450500More0%5%10%15%20%25%30%35%Histogram of Furniture Shipping Charges Percent FrequencyBinsPercentageFigure1: A Histogram plot of shipping charges for percent frequenciesThe histogram plot above shows the distribution of furniture shipping charges based onmail-order business owned by Missy Walters which are presented in percentages. Generally, thedata is highly skewed to the right with most of the furniture shipping prices ranging between 150and 300 – although the prices vary from 123 to 490. Therefore, we can conclude that furnitureshipping prices is not normally distributed. Close to 30% of the customers will pay approximateshipping prices of more than 350 dollars while approximately 70% would pay below 350 dollarsfor every shipment.c)The most appropriate measure of central tendencyIn such as sscenario where the data is not approximately normal, mean is not the bestmeasure of central tendency. Median and mode can be used to explain the best central measure,with mode being used in discrete data where one value has a very high frequency. Median will
GROUP ASSIGNMENT – STATISTICS4be the best measure of central location and quartiles to evaluate the dispersion of the values. Themedian statistic is $228.5, first quartile is $182.75 and third quartile is $295.25.2.Relationship between Demand (Y) and Unit price (X)Figure2: Computer output for regression analysis between Demand and unit pricea)Does unit price (X) significant explain the variation of demand (Y)Demand is the response variable and unit price is the predictorZvalue=BetacoefficientstandarderrorofthecoefficientThe Beta coefficient associated with the unit price in the regression output is -2.137 and astandard error of 0.248. The beta coefficient of the unit price is negative showing that increasingthe price of the commodity leads to reduced demand and vice versa. To test its significance, wecalculate its Z statistic and check the p-value to make the decision. Small p-values which are lessthe significance level shows that the variables is a significant predictor in the model(Aiken,West, & Pitts, 2003).2.1370.248=8.167
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