Understanding Information

Understanding information

Understanding information

The data set consists of variables that are involved in the hospitality trade for the year 2009. Four variables are encountered to find out the best results, total employment cost (dependent variable) has been correlated with other independent variables. Each variable comprises on the 12 different activity levels. The total and average values for each variable are as follow:

Number of enterprises (number)

Total turnover (£ million)

Total purchases of goods, materials and services (£ million)

Total employment costs (£million)

Total

393175

203726

110163

60566

Average

32765

16977

9180

5047

Total Employment Cost and Number of Enterprise

Symmetric Measures

Value

Asymp. Std. Errora

Approx. Tb

Approx. Sig.

Interval by Interval

Pearson's R

.964

.019

11.469

.000c

Ordinal by Ordinal

Spearman Correlation

.986

.017

18.709

.000c

N of Valid Cases

12

a. Not assuming the null hypothesis.

b. Using the asymptotic standard error assuming the null hypothesis.

c. Based on normal approximation.

The correlation result suggests that there exist a good relationship between the two variable i.e. total employment cost and number of enterprise. The magnitude of both correlation methods Pearson and Spearman show that the Total Employment Cost and Number of Enterprise are highly correlated and they also have association between them.

Total Employment Cost and Turn Over

Symmetric Measures

Value

Asymp. Std. Errora

Approx. Tb

Approx. Sig.

Interval by Interval

Pearson's R

.998

.002

44.698

.000c

Ordinal by Ordinal

Spearman Correlation

.993

.014

26.599

.000c

N of Valid Cases

12

a. Not assuming the null hypothesis.

b. Using the asymptotic standard error assuming the null hypothesis.

c. Based on normal approximation.

Correlation result between Total Employment Cost and Turn Over states that the variable are positively and extremely correlated and they posse's strong association (Blinder, 2004). The result is obvious because the theory also says that the more the employment cost and turnover are truly interdependent which means that if one of the factor increase the other will also increase and vice versa.

Total Employment Cost and Total Purchase

Symmetric Measures

Value

Asymp. Std. Errora

Approx. Tb

Approx. Sig.

Interval by Interval

Pearson's R

.993

.005

26.727

.000c

Ordinal by Ordinal

Spearman Correlation

.993

.014

26.599

.000c

N of Valid Cases

12

a. Not assuming the null hypothesis.

b. Using the asymptotic standard error assuming the null hypothesis.

c. Based on normal approximation.

The magnitude of the correlation result suggests that the variables are interdependent and they have a positive a strong correlation i.e. 0.993 which is very good. But as compared to the other variables this relationship is a bit weak as the other variables have shown higher relationship.

If we look at the overall result it can be said that all the variables are interdependent with Total Employment Cost, they posses high correlation and they have strong association (Blinder, 2004). The magnitude of Total Employment Cost and Total Turnover i.e. 0.998 is the best predictor for the total employment cost and also they have the highest correlation of the overall dataset.

Scatter Plot between Total Employment Cost and Total Turnover

The scatter plot between Total Employment Cost and Total Turnover shows a linear trend between the two variables (Bruszt, 2002). The plot indicates a straight line which suggests that total turnover is the best predictor of total employment cost.

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

119.949

168.453

.712

.493

TotalTurnOver

.290

.006

.998

44.698

.000

a. Dependent Variable: TotalEmploymentCost

The regression equation for total employment cost and total turnover can be written as:

Total Employment Cost = 119.949 + 0.290 Total Turnover

This equation can be interoperated as a 1% change in turnover will increase the total employment ...