The Effect of Rainfall of the Great Lakes

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The Effect of Rainfall of the Great Lakes

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The Effect of Rainfall of the Great Lakes

The first data source, by Corral in Home Textiles Today (00) points out that diversity may be a key to growth at OWSphinx. The second data source compares customer satisfaction levels for in-store and on-line shopping. Since a key focus is on creating an on-line, interactive web site, it is important to understand what the strengths and weaknesses could be. Focusing on the business-to-business e-commerce is expected to help the company a great deal.

OWSphinx can utilize this data as supporting evidence of a growing market to help them achieve their ultimate goal of increasing sales by at least 5% within the first 10 days of solution implementation.

The first external data source is based on information collected directly from producers and manufacturers and was collected by the U.S Department of Commerce; Claritas, a market research firm headquartered in Alexandria, VA; and import data collected from, U.S. Customs Service, the U.S Census Bureau and the U.S. International Trade Commission. Kay Anderson, Jennifer Marks, Janice Chamberlain and Cecile B. Corral, all contributing staff members of Home Textiles Today, compiled the data. For our examination of central tendency, we will use the percentages of gain or loss of market share as the focus of our investigation of the first external data.

Average Precipitation

YearJan.Feb.Mar.Apr.MayJun.Jul.Aug.Sep.Oct.Nov.Dec.

in..61.761.74.55.5..61.18.4.8.1.67.8

mm88444464747418087756771

Years Charted 0 Source National Weather Service, San Francisco

Results based on data collected from 161 - 10

1.76Column1

1.74

.55Mean.7

.5Standard Error0.17

.Median.86

.61Mode#N/A

.18Standard Deviation0.60

.4Sample Variance0.6

.8Range1.87

.1Minimum1.74

.67Maximum.61

.8Count1

N = 1, Population Mean = .7, Standard deviation = 0.60

Null Hypothesis = .7" rain per month

Alternative Hypothesis is not = .7" rain per month

z Test = (X Pop. Mean)/ (Std. Dev./Sq.root of N) = 0.8

Reject the Null Hypothesis if z 1.6 or -1.6

p-value = .7

BinFrequency

1.

.7

.

More0

For purposes of the data selected for this report, the market segment was a purposive sample meeting 5 specific criteria (1) non-bath, () accent and area rugs () up to 6 by , (4) with price points below $1,000, and (5) sold through the specific retail classes of trade described. The data is measured on a ratio scale, represented by total sales (in millions of dollars) and percent of the market represented by specific groups. The information collected is reflected on annual reports filed by participants and is considered to be quite valid. It also fairly reliable, for the same reason, though a longer time period would better reflect and long-term or unknown factors that may reflect upon the reliability of the data.

To analyze the data above, the chart below illustrates the calculated values for mean, median and mode as descriptions of the central tendencies of this data set.

The histogram bellows illustrates the left skewed, or positive, tendency of the data set relative to the mean value.

As a result of data analysis, OWSphinx should prioritize discount department stores and home improvement centers, as the first customers to benefit from the implementation of the corrective actions. The analysis of the research data also shows where OWSphinx should not focus any corrective actions. In fact, the analysis indicates that OWSphinx should leave the segment of retail rug outlets that include furniture stores, floor covering shops and specialty stores. The analysis of the data showed this segment of the market has realized a 46% reduction in sales volume. The value of utilizing market data, to it's fullest potential, can be a catalyst in assisting OWSphinx in implementing their corrective action plan.

References

Corral, C. B. (00). Tug sales up despite difficult '01. Home Textiles Today.

Retrieved June 14, 00 from http//www.hometextilestoday.com/index.asp?layout=article&webzine=htt&publication=htt&articleid=CA116

Cho, Y. ( 00) The effects of post purchase evaluation factors on on-line vs. in- store customer complaining behavior. Doctoral dissertation, Rutgers University, Newark, NJ, 00. Retrieved June 16, 00, from http//wwwlib.umi.com/dissertations/order_pickup/prod/500e45bbd005716fae66455b6/61485/08416/04648.PDF

Pelosi, M., Sandifer,T., Sekaran, U., (000) Research and evaluation for business. [UOP Special Edition Series] New York Wiley.

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