DECISION MAKING

Quantitative Data Analysis and Decision Making

Quantitative Data Analysis and Decision Making

Introduction

The study is related to the decision making which particularly focuses on various factors that are important for the USA. In this context, various variables are considered that include factors of free on board, average price per unit, duty per unit, average gross margin, landed cost per unit and freight per unit. These indicators are important to study as the analysis of the data pertained to USA which will reveal vital and imperative results.

Analysis

Statistics

O/S currency

Exchange Rate

Freight / Unit ($.c)

Duty / unit

Landed Cost /unit

Aver Price/ unit

Stock on hand Current

Quantity sold last 6 months

Av. Gross Margin %

FOB $AU

N

Valid

494

494

489

494

494

494

494

494

494

494

Missing

0

0

5

0

0

0

0

0

0

0

Mean

4.7639

.9496

1.3555

.1808

6.5380

42.6421

128.4453

3547.7287

.8604

5.0150

Median

2.1400

.9500

.4900

.0600

2.9300

37.0100

3.0000

42.0000

.9300

2.2500

Mode

.00

.95

1.83

.00

1.27

73.99

.00

.00

.93

.00

Std. Deviation

7.20484

.00636

2.95774

.35788

9.94469

28.26603

353.36641

11154.37083

.15885

7.58372

Variance

51.910

.000

8.748

.128

98.897

798.968

124867.817

1.244E8

.025

57.513

Skewness

2.744

- 15.668

3.886

3.373

2.769

2.310

5.334

4.706

- 2.474

2.744

Std. Error of Skewness

.110

.110

.110

.110

.110

.110

.110

.110

.110

.110

Kurtosis

7.539

244.484

15.477

11.709

7.862

6.358

38.102

24.850

6.267

7.540

Std. Error of Kurtosis

.219

.219

.220

.219

.219

.219

.219

.219

.219

.219

Range

42.60

.10

22.61

2.24

69.69

142.52

3588.00

85297.00

.89

44.84

Minimum

.00

.85

.00

.00

.00

7.49

.00

.00

.11

.00

Maximum

42.60

.95

22.61

2.24

69.69

150.01

3588.00

85297.00

1.00

44.84

The result of the frequency table is showing the mean and other values of the all the variables that are used in analyzing the data. The most important values of the above table that is means and the standard deviation of the variables which are important to study as these values are providing the accuracy of the data which has been gathered from the USA. From the above table, it is observed that the standard deviation of the quantity sold in last 6 months is high as compared to the other variables. Furthermore, it shows that in USA, the mean of the quantity sold in last 6 months is 3548 which is high.

To find out the correlation among Freight / Unit ($.c) per unit, Duty / unit per unit and landed cost per unit

Correlations

Freight / Unit ($.c)

Duty / unit

Landed Cost /unit

Freight / Unit ($.c)

Pearson Correlation

1

.505 **

.777 **

Sig. (2 - tailed)

.000

.000

N

489

489

489

Duty / unit

Pearson Correlation

.505 **

1

.883 **

Sig. (2 - tailed)

.000

.000

N

489

494

494

Landed Cost /unit

Pearson Correlation

.777 **

.883 **

1

Sig. (2 - tailed)

.000

.000

N

489

494

494

**. Correlation is significant at the 0.01 level (2 - tailed).

The above result for the data shows that there is correlation among freight per unit, duty per unit and landed cost per unit. In addition to this, the value of the Pearson correlation coefficient shows that the value is in positive that is 0.505 for duty per unit and 0.777 for landed cost per unit as the value of Pearson correlation coefficient is significant that is it is are less than 0.5 which shows that the value is significant. In this context, the correlation is a statistical relationship between two or more random variables (or variables that you can with some degree of accuracy consider acceptable as such). At the same time changing the values of one or more of these quantities are accompanied by systematic changes in the values of one or several other variables. The mathematical measure of the correlation of two random variables is the correlation ratio, or the correlation coefficient. In the event that a change in one of the random variable does not lead to a natural change in the other random variable, but it leads to a change in the other statistical characteristics of the random variable, then such a relationship is not considered a correlation, although a ...