Excel

Table of Contents

Executive summary 3

3Business problem

Statistical problem 3

Analysis 4

4Q1; Descriptive statistics for the prices of male and female products

Q2. Descriptive statistics for prices for twin, 3-blade and 5-blade cartridges 5

Descriptive statistics for prices for different countries 5Q3.

Q4. Difference in the mean prices for different countries 6

7Q5; mean price of twin, 3-blade and 5-blade cartridges

Q6; difference in the mean prices for different countries 8

Conclusion 9

Implications 9

Reference list 9

Executive summary

The research analysis focuses on making an investment decision of whether to produce the new product (Razor) or not. The investment decision is based on the result of the excel output generated. The output of the excel data provides that the price of razor for females are high on average since, it depicts a median of 6.5 unlike a median of 6 for men. The result further reveals that there will be high demand of the product in USA. The report will therefore centre on providing an analysis and comprehend the link between the price and the product in term of gender, regions and types of razor to be manufactured. The research analysis employed the use of descriptive statistics and single factor ANOVA in understanding the need for new product in the market and recommend on the best alternative to undertake in order to maximize return and profit to the company within the shortest time and cost.

Business problem

The company is facing the problem of whether adding a new production line of producing the new type of razor blades and the need for the product in the market. To provide the best investment decision, there is need to understand the product viability which will entail both internal and external factors (William Petty, 2015). The external factors entail the analysis of the demand, the effect of competition and supply of the product to various regions and gender. Internal factors will comprise understanding of whether the current production capacity efficient or whether there is need to add new production line, the current level of skills labors and availability of the finance to fund the new product.

Statistical problem

The analysis entails the use of data analysis tool pack to generate the descriptive statistic in terms of mean, mode, median,, range, maximum, minimum, skewness and kurtosis of the distribution and to develop an hypothesis testing to comprehend whether there is difference in price of the product in difference regions, gender and based on number of cartridge and blades and forming a conclusion based on the result of the descriptive statistics and hypothesis testing (Wang, 2014).

Analysis

Q1; Descriptive statistics for the prices of male and female products

The outcome for the de3scripotive statistics from the excel data analysis tool pack are explained in details as follows.

Excel

From the histogram above, it is evident that the price for male is high but on average as depicted by the median; the price of the females is high since, the median for the females is 6.5 while for the males it is 6. This means that, the demand for the razor blade is high for females

Q2. Descriptive statistics for prices for twin, 3-blade and 5-blade cartridges

Excel 1

It is evident from the above graph of price frequency by cart that, the price of razor will be high for the three blades. This would imply that the demand for the three blade razor should be met by producing more of the three razor blades. Other than this, there is need to have an optimal mix with the remaining product of twin blade and 3 blade razor since, both depict high demand with twin blade being on a high demand as compared to 3 blade razor (Schuster, 2015).

Q3. Descriptive statistics for prices for different countries

Excel 2

From the graph above for price frequency by different countries, it can be observed that the price for price for USA is high as compared with the price in France. The implication is that, the company will have more of its new product being supplied to USA then to France and then tom other countries in that sequence in order to maximize profit and meet the demand for the new product (Schuster, 2015).

Q4. Difference in the mean prices for different countries

We will use the single factor ANOVA test to understand the price of the product as follows

Hypothesized Difference

Level of Significance

Population 1 Sample

Sample Size

Sample Mean

Sample Standard Deviation

Population 2 Sample

Sample Size

Sample Mean

Sample Standard Deviation

Intermediate Calculations

Population 1 Sample Degrees of Freedom

Population 2 Sample Degrees of Freedom

Total Degrees of Freedom

Pooled Variance

Standard Error

Difference in Sample Means

t Test Statistic

Upper-Tail Test

Upper Critical Value

Do not reject the null hypothesis

Variance

11.72941

10.89721

Source of Variation

Between Groups

319.3423529

319.3424

33.05016

2.25E-06

4.149097

Within Groups

309.1952941

9.662353

628.5376471

The result of the ANOVA test depict that that p-value will be 0.1468 which is less than the t critical 1.6639 hence we accept the null hypothesis. The implication is that, there is no difference of mean for price for different countries. This is because, under the single factor ANOVA test, the t statistics which is less than t critical will reject the null hypothesis (Ehrhardt, 2008).

Q5; mean price of twin, 3-blade and 5-blade cartridges

Test Statistic;

  • Null Hypothesis; there is no Difference in the mean price of twin, 3-blade and 5-blade cartridges

  • Alternative hypothesis; there is Difference in the mean price of twin, 3-blade and 5-blade cartridges

  • Significance level;5%

Variance

171.4000

243.9000

129.4000

Source of Variation

Between Groups

Within Groups

1431.1019

Level of significance

It can be concluded that, the alternative hypothesis is rejected and accept the null hypothesis since, the p values is 0.5009 which is less than the t critical value of 0.6974. The conclusion is that, we accept the null hypothesis since; there is deference of mean between prices of the products (Albright, 2016).

Q6; difference in the mean prices for different countries

Test Statistic;

  • Null Hypothesis; there is no difference in the mean prices for different countries.

  • Alternative hypothesis; there is difference in the mean prices for different countries.

  • Significance level;5%

ANOVA: Single Factor

Variance

Source of Variation

Between Groups

1187.2942

593.6471

176.7070

Within Groups

268.7600

Level of significance

The above ANOVA test statistics depicts that the p-values is 0.3030 which is less than 3.1108 hence we accept the null alternative and conclude that there is difference in the price for different countries

Conclusion

After a comprehensive analysis of the demand of the new product, it can be summarized that, the company should proceed with the production of new razor blades since; it is evident that the company is going to realize profit as a result of high demand of the product in different countries, in different types and based on the gender. The company will therefore have returns within the shortest time from investing in the new product. The conclusion is that, the new product must be produced by the company since; there will be positive returns from investment.

Implications

The implication I that, positive returns will be realized from investment. The company needs to consider both internal and external factors that will affect the attainment of the profits from the sale of the new products. This entails the need for good source of finance to fund production of new product, the need for new production line as well as understanding whether new labor source will be required. The company will face fresh competition as a result of new product and consequently there is need to invest on advertisement in order to ensure that the product reach wide coverage within the shortest time and at low cost. This will lead to customer look in and competitor lock out hence making the company the price leader of the new product in the market.

Bibliography

Albright, C. (2016) Business Analytics: Data Analysis & Decision Making — Page 230, London : Cignage Learning.

Ehrhardt, M. (2008) Corporate Finance: A Focused Approach — Page 554, london: Cingage Learning.

Hwang, C.-L. (2012) Group Decision Making under Multiple Criteria: Methods and Applications, Sydney: Springer.

Jerry, W. (2009) Managerial Accounting: Tools for Business Decision Making, London: Jonh Wiley.

Palepu, K. (2007) Business Analysis and Valuation: Ifrs Edition — Text Only — Page 11, New York.

Schuster, U.G.‎.N.&.‎. (2015) Investment Appraisal: Methods and Mode, New York: Cingage Learning.

Tessa Hebb, ‎.P.H.‎.G.F.H. (2015) The Routledge Handbook of Responsible Investment.

Wang, S. (2014) Chinese Strategic Decision-making on CSR.

William Petty, ‎.T. (2015) Financial Management: Principles and Applications — Page 705, London: Springer.