Statistical Tools and Data Analysis
Essay by brett zurbrick • April 10, 2016 • Course Note • 665 Words (3 Pages) • 1,604 Views
Statistical Tools and Data Analysis
Brett Zurbrick
QSO-510
02-06-2016
To understand the needs of A-Cat Corporation with regard to the required amount of transformers and voltage regulators as it corresponds to the sale of refrigerators we must take into account multiple statistical analysis tools. These tools include the ANOVA analysis as provided by our operations manager, descriptive statistics generated for years 2006 thru 2010, and a forecast so as to look into the future to try and predict transformers needed for voltage regulators used in refrigerators. Using these statistical analysis should better inform A-Cat Corporation of current production as well as provide the company the ability to understand the demand for their product now and into the future. This will in turn allow for better business planning, cost savings, and production practices.
The operational data being investigated and analyzed is provided via the operations team at A-Cat Corporation. The data being measured allows for comprehensive analysis that takes raw data and returns information that can be used to better company performance and more fully understand the business as whole. The statistical tool used, such as Excel’s Statistical Tool Pack will help us evaluate the performance of A-Cat Corporation. This tool is widely available, relatively easy to use, and extremely robust.
By evaluating the statistical description of refrigerator sales from the year 2006 thru 2010 and the transformer requirements as seen below we can better understand the means and ranges required to fully understand the business.
Sales of Refrigerators |
| Transformer Requirements |
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Mean | 5371.2 | Mean | 2924.9 |
Standard Error | 304.1271514 | Standard Error | 103.4292257 |
Median | 5221.5 | Median | 2844 |
Mode | #N/A | Mode | #N/A |
Standard Deviation | 1360.097969 | Standard Deviation | 462.5495592 |
Sample Variance | 1849866.484 | Sample Variance | 213952.0947 |
Kurtosis | -0.295177496 | Kurtosis | -1.00852493 |
Skewness | 0.454044834 | Skewness | 0.187178159 |
Range | 5041 | Range | 1566 |
Minimum | 3291 | Minimum | 2208 |
Maximum | 8332 | Maximum | 3774 |
Sum | 107424 | Sum | 58498 |
Count | 20 | Count | 20 |
Confidence Level(95.0%) | 636.5454435 | Confidence Level(95.0%) | 216.4798574 |
By using this data and that from the ANOVA showing details for the years 2006 thru 2008 below we can understand the underlying trends in the business. Namely that the average mean is increasing as time goes by, inferring that more refrigerators are being sold and thus more transformers for the voltage regulators are needed for the manufacture of new refrigerators to be brought to market.
ANOVA: Single Factor | ||||||
SUMMARY | ||||||
Groups | Count | Sum | Average | Variance | ||
2006 | 12 | 9614 | 801.1666667 | 7020.515152 | ||
2007 | 12 | 10784 | 898.6666667 | 18750.06061 | ||
2008 | 12 | 11884 | 990.3333333 | 21117.87879 | ||
ANOVA | ||||||
Source of Variation | SS | df | MS | F | P-value | F crit |
Between Groups | 214772.2222 | 2 | 107386.1111 | 6.870739001 | 0.003201767 | 3.284917651 |
Within Groups | 515773 | 33 | 15629.48485 | |||
Total | 730545.2222 | 35 |
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In this instance we can see that the F and P values in the ANOVA have changed considerably showing that there has indeed been a change in the number of transformers being produced in this time frame, the trend of which clearly, the trend of which clearly indicates that as time passes production has increased to keep pace with that of refrigerator sales.
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