Task 3: Using three statistical techniques to analyze data

Decision making is fundamental role to survive the business and to make solutions for the problems of declining sales and poor financial performance. Analyzing data is required to make decisions in order to solve these problems. Additionally, mathematical and statistical techniques which are provided to evaluate data from different sources and to predict the outcomes of future events. These statistical techniques should be used to measure data that can be integrated efficiently in the overall outcome measures. There are two methods: quantitative method and qualitative method to be used. The following methods are associated with quantitative method which help in analyzing data and making decisions for the proposed projects to resolve the problem of H&M declining sales and poor financial performance.

Time Sale (SEK, B)

Year Quarter

2015

I 40

II 46

III 46

IV 43

2016 I 44

II 47

III 49

IV 53

2017 I 47

II 51

III 51

IV 50

Quantitative methods

Babie (2010) described quantitative data as “the numerical representation and manipulation of observations for the purpose of describing and explaining the phenomena that those observations reflect”. Quantitative methods give emphasis to measurements and statistics, mathematical analysis of data gathered through questionnaires or surveys or using existing data. Quantitative research focuses on collecting numerical or invariable data, helped by calculators or spreadsheets to give details for specific phenomenon. Technically, this research handles with numbers, theory, and logic. Mathematical techniques are used to analyze in operations and inventory management, marketing and sales forecasting, and finance and accounting to quantity numeric data. And this method can be used by the company to generate the performance in areas, including marketing, operations and human resources.

Univariate Data Analysis

This is the simplest way to analyze data. Data is collated for intentions to solve the problem. Univariate data is used to answer only one variable characteristic rather than problems between variables. The H&M group can adopt this analysis to describe its problems of declining sales. For example, collect data, review data, and find the shortcomings in this data.

Time (x) Sales (y) xy x^2 y^2

1 40 40 1 1,600

2 46 92 4 2,116

3 46 138 9 2,116

4 43 172 16 1,849

5 44 220 25 1,936

6 47 282 36 2,209

7 49 343 49 2,401

8 53 424 64 2,809

9 47 423 81 2,209

10 51 510 100 2,601

11 51 561 121 2,601

12 50 600 144 2,500

??x=78 ???y=?567 ???xy=?3,805 ???x^2=?650 ???y^2=?26,947

Summary Measures- Means, Medium, Mode

Mean (Average value) of sales

Mean, y? = (??y)/n

= 567/12

= 47.25 (SEK B)

Medium sales,

Data array: 40, 43, 44, 46, 46, 47, 47, 49, 50, 51, 51, 53

Medium= 47 (SEK B)

Mean > Medium

The distribution of sales of positively skewed. So, the sales are decreasing.

1.2 Measure of Dispersion

Range = largest value – smallest value

=53-40 = 13 (SEK B)

Standard deviation

S = ?(??y^2/n+(y ? )^2 )

=?(26,947/12+2,232.56)

= ?(2,245.58+2,232.56)

= ?4,478.14

= 66.92 ($ B)

Coefficient of variation = S/ y? × 100

= 66.92/47.25 × 100

= 142

Bivariate Data Analysis

For two variables, the company can use Bivariate Data analysis. The analysis is used to analyze two items which are related with each other. For instance, the product sales compared to the time. The analysis is practically adopted by many companies in these days since it can be used to predict if they have any problems within the company. The H&M group can use “Correlation Analysis” to put a figure on the relations between two variables and “Regression Analysis” to forecast the future events by using the linear regression equation of dependent variable (Sales) on independent variable (Time). Between this two the dependent variable is the main character the company tries to predict for its problems. The analysis can help to solve the problems: Which is the most important? Which items can be neglected? How many certainties does the company get about these facts?

Predictive

Correlation Analysis – to show the strength of relationship between two variables

r = (n ???xy-(???x)(???y)???)/?(n???x^2-?(???x)??^2?n???y^2-?(???y)??^2?)

= (12(3,805)-(78)(567))/?(12(650)-(?78)?^2 12(26,947)-(?567)?^2)

= (45,660-4,4226)/?(7,800-6,084323,364-321,489)

= 1434/?(1,716×1875)

= 1,434/?3,217,500

= 1,434/1794

=0.8

The time point and the sales are positively correlated.

Regression analysis to forecast the future sales on time

y = a + bx

Where y = sales

x = time point

a and b are unknown constants.

b = (n???xy-???x??y??)/(n??x^2 -?(??x)?^2 )

a = y ? – b x?

b = ((12×3,805)-(78 ×567) )/((12×650)-(?78)?^2 )

= (45,660-44,226)/(7,800-6084)

= 1,434/1,716

= 0.84

a = (??y)/n – b (??x)/n

= 567/12 – 0.84 × 78/12

= 47.25 – 5.46

= 41.54

The estimated linear regression equation for sales on time is,

? = 41.54 + 0.84x

Estimate sales for the fourth quarter of 2018 will be, x = 16

? =41.54 + 0.84 (16)

=41.54 + 13.44

=54.98 (SEK B)

To solve the problem of finance and accounting, the H&M group can use certain methods to find the accounting rate of return and payback period, and to know net present value.

Accounting rate of return and payback period

Accounting Rate of return (ARR) is used to make decisions on situations which the company is in dilemma to decide whether it should invest in the project or not. This is a formula which is described as percentage.

Accounting rate of return = (Average Revenue)/(Initial Investment) × 100

Payback period

Payback period represent the time required to get the initial investment in return by generating cash flows. This can be used to assess the risk of suggested project and to analyze the investment in case the H&M group can accept the investment with shorter payback period and turn down the longer period in making project to solve the problems of financial performance within the company. The payback method is used to calculate the payback period, which is finalized in years and months.

Payback Period = Initial Investment ÷ cash flow per period

But there is one condition that the annual cash flow cannot always be the same, so the company need to determine the cumulative cash flow per year. In this condition, the following method can be used,

Payback Period = A + B

C

Where, A = the last period with a negative cumulative cash flow B = the absolute value of cumulative cash flow at the end of the period of A C = the total cash flow during the period after A

For example,

Year cash flow cumulative cash flow ( SEK B)

0 (10,000) (10,000)

1 2,000 (8,000)

2 4,000 (4,000)

3 5,000 1,000

Payback Period= 2 years + 4,000/5,000 × 12 = 2 years and 9.6 months = 2 years and 10 months

Net Present Value

Net present value method is used to determine the budgeting project and cost reduction program in finance and accounting, and these project will be accepted or rejected. The cash flows in this this analysis is discounted to regulate the risk of investment.

In this analysis, If NPV>O, the project will be accepted

If NPV