Bsiness statistic - Assignment Example

For example, when the factors that are contributing most to the overhead costs are known, it becomes easy to control such costs. This report will involve analysis of different variables that are believed to affect overhead costs, including number of setups, machines hours and labour hours. Some of the methods of analysis that will be used include descriptive statistics, regression analysis, and use of histograms and graphs. Section A - characteristics of all the variables Calculating measures of location (averages) and dispersion (variation) N Mean Std.

Deviation Variance Overhead costs 24 172.79 17.939 321.824 Direct Labour hours 24 1134.67 64.629 4176.928 Machine hours 24 1402.58 213.135 45426.514 No. of setups 24 201.42 13.990 195.732 Valid N (listwise) 24 Table 2: descriptive statistics (averages and variation) Using all 24 months’ data to construct a frequency distribution and histogram for the machine hours Machine Hours Frequency 1000 0 1100 5 1100 0 1200 1 1200 0 1300 2 1300 0 1400 4 1500 3 1600 6 1700 2 1800 1 Table 2: Frequency Distribution Table Figure 1: Histogram for the machine hours Estimating the median and other descriptive statistics for the machine hours Column1 Mean 1402.

583 Standard Error 43.50599 Median 1428 Mode 1300 Standard Deviation 213.135 Sample Variance 45426.51 Kurtosis -0.97697 Skewness -0.22011 Range 710 Minimum 1060 Maximum 1770 Sum 33662 Count 24 Table 3: Median and Other Descriptive Statistics for machine hrs A brief Report Determination of descriptive statistics is very essential in decision-making regarding cost. Among the four variables, the highest level of dispersion was reported in machine hours, as shown by the standard deviation and variance, implying that use of machines is likely to significantly affect variations in overhead cost.

Number of set ups have the least dispersion, possibly meaning that this variable may not significantly cause cost variation (Table 2). Table 2 shows the grouped frequency histogram for the machine hours, where it is evident that most of the hours lie between 1001 to 1100 and 1501 to1600. The shape of the histogram exhibits a bimodal distribution or rather it has two peaks. This is a problem that results from stratification and it means that the data could have originated from two different sources.

It is, therefore, important to identify these sources and analyse the data separately if appropriate. Figure 3 shows the descriptive statistics for the machine hours. The minimum and the maximum values are very useful in quickly identifying the range between which hours fall, which in this case is 1060(min) and 1770(max). The standard error gives the extent to which the distribution is exposed to sample error, which in this case amounts to 43.5 (Mann, 1995). Section B Graphs and analysis of the linear relationships in the variables related to the overhead costs.

Figure 2: OH costs vs. direct labour hours Figure 2: Overheads costs are directly related to the direct labour hours, which means that an increase in direct labour hours leads to an increase in overhead costs. The equation y=2.5352x +