Assignment Economics: Regression Analysis

Added on - 28 May 2020

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Executive Summary:The analysis is based on a sample of 60 American sales data. The results of the analysisindicates that, the average order quantity for 60 customers is about 24.31 and variationsin average quantity is about 15.14. The customers who buy the products are mostlybelongs to thehome office type. The average sales of itemsis about 1716 and thecustomers mostly prefer regular Air mode delivery system to deliver the sales items.The average shipping cost is the delivery for the customers is about $12.57 and deviationin the shipping cost form average shipping cost is about $15.93, the customer’s mostlypreferred the eastern region as a delivery space for delivery of selling items and theaverage number of days for shipment of sold items is about 1.71.The priority order ofcritical type have lower shipping cost comparison to the low priority order type. The averagesales order for the western states and the eastern states are nearly equal, so the customerswho are living in the western state and eastern are not facing problems in the deliveryspace.
Introduction:The analysis is based on the Australian Sales data of 2002 orders. It is mentioned that toselect the sample of 60 observations from Australian Sales data use the random numbertable. The purpose of the report based on the summary statistics of quantitative variablesand graphical representation of the all qualitative variables. The report includes thefollowings:1. Whether average sale amount order for home office customers for sample orders is arepresentative of population average sales orders.2. Whether the sampleaverage shipping cost for sample ordersrepresents the populationaverage shipping costs.3. Whether thecritical priority order would have higher shipping costs than low priorityorder.4.Is theaverage sales order are different for Eastern andWestern regions?5. It also includes the prediction of sales by using the order quantity.UseZ-test to do the analysis whether the amount of orders for average sales in sample ofhome office customers represents the amount of orders for population average sales forhome office customers, and whether sampleaverage shipping costs for all sample ordersrepresents the populationaverage shipping costs for all sample orders.Use two sample independentt-test, to do the analysis that thecritical priority orderwould have higher shipping costs comparison to the low priorityorder, and whether themean sale orders are different for Eastern andWestern regions.The correlation technique will be used to know about the relationship between sales andorder quantity, and to predict the sales by using order quantity, the regression techniquewill be used.Analysis:To select a random sample of size 60 from the 2002 orders, use random number table.The random number table includes the values in a random order, so to get the sample ofsize 60 from the 2002 orders, select only that random numbers which are less than 2002and skip the other numbers. Thus, the 60 order numbers will be observed form the tablewhich are less than 2002. Now, write the data of selected 60 numbers fromAustralianSales into a new excel sheet. The sample of 60 orders will be generated.Now use the sample data to calculate the summary statistics for quantitative variables andto draw the graphical summary for the qualitative variables. The summary statistics foreach of the variable is given below:1.Order priorityindicates importance of order, the value indicates a Critical order, thevalue 3 indicates a high order, the value 2 indicates a medium order, the value 1indicatesa low order and the value 0 indicates a not specified order. So the variable order priorityis a qualitative variable. The frequency of each variable and the bar graph is shownbelow:Variable\StatisticNbr. ofobservationsNbr. ofcategoriesModefrequencyCategoriesFrequencypercategoryOrder Priority60516016.00
17.00213.00315.0049.00According to the bar graph, maximum frequency is obtained for the not specified ordersand for the high priority order.2.Order quantity indicates importance number of items within the order. So the variableorder quantity is a quantitative variable. The summary statistics is shown below:Order QuantityMean24.3166Median28Mode6Minimum2Maximum50Range48Variance229.2370StandardDeviation15.1405Coeff. ofVariation0.6226The average order quantity is about 24.31, the minimum number of order is 2 and themaximum number of order is 50. The deviation in the order quantity form averagequantity is about 15.14.
3.Sales indicates sales of items. So the variable sales is a quantitative variable. Thesummary statistics is shown below:SalesMean1716.6916Median403.6597Mode43.29Minimum2.24Maximum29345.27Range29343.03Variance11517187.07StandardDeviation3393.6981Coeff. ofVariation1.9768The average sales is about 1716, the minimum number of sales is 2 and the maximumnumber of sales is 29435. The deviation in the sales form average sales is about 3393.4. Ship modeindicates shipping mode of delivery. The frequency of each variable and thebar graph is shown below:Variable\StatisticNbr. ofobservationsNbr. ofcategoriesModefrequencyCategoriesFrequencypercategoryShip Mode60342142.0025.00313.00According to the bar graph, maximum frequency is obtained for regular Air mode ofdelivery.
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