Survey of Employee Satisfaction Essay

essay A
  • Words: 1732
  • Category: Database

  • Pages: 7

Get Full Essay

Get access to this section to get all the help you need with your essay and educational goals.

Get Access

Bus409 Managing Finance and Statistical Data – Assignment 1

Introduction ………………………………………………………………………………………… …

Undertaking 1 – Sampling

Undertaking 2 – Graphs and Calculation

Undertaking 3 – t-test

Undertaking 4 – Correlation and Regression

Undertaking 5 – Written Analysis

Appendix 1 – Copy of random figure tabular arraies used

Appendix 2 – Sample of 30 records used

Introduction

The sample of informations analysed in this assignment is concerned with study consequences for 363 employees from an administration based in 8 different metropoliss. In this assignment descriptive and illative statistical analyses were practiced. The informations were collected as a footing for analysis. Descriptive statistics used for the populations, analyzing, correlativities between your graduated tables, and illative analysis utilizing appropriate t-tests or analyses of discrepancy.

The first set of analyses of information is called descriptive statistics. The end of this signifier of analysis is to make quantitative sum-ups of the dataset. Descriptive statistics inform on the mean measurings of a graduated table or point, how much these measurings vary across observations, the scope of measurings, and other facets cognizing about informations. This signifier of analysis besides includes making ocular representations of your informations as Bar chart, histogram and cumulative frequence curve and spread secret plans. Ocular tools help the research worker identify anomalousnesss, outliers, and tendencies in informations.

In this assignment variable were used to prove hypotheses about informations utilizing illative trials. The trials used to place how categorical variables affect graduated tables or response variables.

The concluding measure in this assignment shows how the graduated tables and points of informations correlative with each other. The end of looking at correlativities is to place relationships between measurings and suggest possible causal relationships. For case, how much employee like workplace and how they rate working status runing from 1 ( low satisfaction and low importance ) to 5 ( high satisfaction and high importance ) .

Undertaking 1 – Sampling

The information was sampled utilizing a set of random figure tabular arraies bring forthing from the Excel. A random figure tabular arraies to randomly choose a sample of 30 employees from the 363 records.

A transcript of the random figure tabular arraies used and the sample of 30 records can be found in the appendix of this assignment

Undertaking 2 – Graphs and Calculation

Comparison of Employment Status and Recommend Organisation

Organization recommendation by employment type and figure of employees variables were chosen for comparing. These variables were taken from 30 employees random figure tabular array ( see appendix 2 ) . A chart was created utilizing those variables to visualize the comparing of Employment position and Recommendation.

Recommend no

Recommend yes

Causal

2

6

Permanent wave

4

18

The Charts above shows that 18 Employees who are Permanent and 6 who are Casual recommend yes. On the contrary, 4 Permanent and 2 Casual employees recommend no. There is besides a important difference can be visualised between positive and negative recommendation. The entire figure of positive recommendation is 24 ( 80 % ) out of 30. On the other manus, the combination of negative recommendation is 6 ( 20 % ) out of 30 ; which is one fifth of the entire participant.

Satisfaction with Working Conditionss

In order to cipher frequence, satisfaction of working status mark is used from a random figure tabular array which shows in appendix 2. The sores were taken into lowest to highest and bins were calculated in order. In order to cipher the frequence, a expression of frequence “=FREQUENCY ( G2: G31, G35: G40 ) ” was used. Centers were calculated by figure taken from tonss and bins by choosing their in-between figure manually. The histogram was created utilizing frequence Numberss in excel with 2D clustered column. Then from informations series spread breadth reduced to 0 % to make a complete histogram.

Frequencies utilizing Bins

Tonss

Bins

Frequency

Mid-points

2.0 –

2.5

1

2.25

2.5 –

3.0

5

2.75

3.0 –

3.5

7

3.25

3.5 –

4.0

4

3.75

4.0 –

4.5

9

4.25

4.5 –

5.0

4

4.75

Formula

Tonss

Bins

Frequency

Mid-points

2.0 –

2.5

=FREQUENCY ( G2: G31, G35: G40 )

2.25

2.5 –

3.0

=FREQUENCY ( G2: G31, G35: G40 )

2.75

3.0 –

3.5

=FREQUENCY ( G2: G31, G35: G40 )

3.25

3.5 –

4.0

=FREQUENCY ( G2: G31, G35: G40 )

3.75

4.0 –

4.5

=FREQUENCY ( G2: G31, G35: G40 )

4.25

4.5 –

5.0

=FREQUENCY ( G2: G31, G35: G40 )

4.75

Histogram

The histogram above shows employee figure of frequence distribution in relation to satisfaction with working status. Tonss between 2.5 to 3.5 and 4.0 to 4.5 are rather frequent. On the other manus, tonss between 3.5 to 4.0 and 4.5 to 5.0 are somewhat lower but every bit balanced. And score 2.0 to 2.5 is a really low graduated table. Finally, due to the big value, the histogram is somewhat skewed to the left, or negative skewed. Without this value, the histogram would be moderately symmetric.

Accumulative Frequency Curve for Satisfaction with Working Conditionss

The cumulative frequence is the running sum of frequences. On a graph, it is represented by a cumulative frequence polygon, where consecutive lines connect to the cumulative frequence curve. These informations were used to pull a cumulative frequence polygon by plotting the cumulative frequences against the category. Accumulative frequence was calculated utilizing frequence Numberss which were created earlier.

Class

Accumulative Frequency

Bins

up to 2.5

1

2.5

up to 3.0

6

3.0

up to 3.5

13

3.5

up to 4.0

17

4.0

up to 4.5

26

4.5

up to 5.0

30

5.0

Accumulative Frequency Curve

The graph above shows a smooth curve. The cumulative frequence graph above illustrates employees satisfaction with working conditions. By pulling horizontal lines it represents first quartile of the entire frequence, 2nd quartile of the entire frequence, 3rd quartile of the entire frequence, can read estimations of the lower quartile, average and upper quartile from the horizontal axis. Though here a set N value nowadays, the undermentioned computation is done in order.

Table 1. Formula

Lower quartile =

n+1

Thursday value

4

Median =

n+1

Thursday value

2

Upper quartile =

3 ( n+1 )

Thursday value

4

Interquartile scope =

Upper quartile – Lower quartile

Semi-interquartile scope =

Interquartile scope

2

Though there are 30 values ; n=30, is an even figure, from the undermentioned expression ;

  • Lower quartile = 7.75 th value ; which would be 2.62
  • Upper quartile = 23.25 th value ; which would be 3.84
  • Median = 15.5 th value ; which would be 3.28 ( agencies median would be 15 Thursday and 16 Thursday values average ) .
  • Interquartile scope ( 3.84 – 2.62 ) =1. 22 and
  • semi-interquartile scope ( 1.22/2 ) =0.61

Statistical Calculations

The below statistical computations shows that mean 6.07 for length of services is exact reply, whereas median is 3. There is a big difference between mean and average because of utmost value e.g. 34

The mean and median for the satisfaction of working conditions are 3.79 and 3.85 severally. These are good tonss out of five. And 4.12 and 4.15 are the mean and median for the importance of working conditions at the same time. These are more good tonss out of five.

Length of service( old ages )

Satisfaction ofWorking conditions

Importance of

working conditions

3

2.8

2.7

1

3.7

3.9

18

2.9

3.1

14

3.2

3.9

3

3.2

3.7

13

2.4

4.3

9

3.4

4.0

2

4.7

3.9

8

3.3

4.8

5

2.9

3.4

5

3.7

3.5

4

2.9

4.2

0

4.1

4.1

14

4.4

4.5

3

4.0

4.0

3

4.2

4.2

1

3.5

4.0

34

5.0

5.0

1

4.3

3.1

1

4.2

3.9

3

3.2

4.9

0

4.5

4.8

1

4.5

4.4

2

4.3

4.2

8

4.8

5.0

1

4.4

4.5

10

4.0

4.4

10

3.4

3.9

4

2.9

4.6

1

4.9

4.7

Mean

6.07

3.79

4.12

Madian

3.00

3.85

4.15

Standard Deviation

7.16

0.72

0.58

Formulas Used

Mean

=average ( B2: B31 )

=average ( C2: C31 )

=average ( D2: D31 )

Median

=median ( B2: B31 )

=median ( C2: C31 )

=median ( D2: D31 )

Standard Deviation

=stdev ( B2: B31 )

=stdev ( C2: C31 )

=stdev ( D2: D31 )

Remarks: consequences are dependable

Mean and Standard Deviation of a Frequency Distribution

Statisticss expressions are: mean, =and standard divergence, i?? =

Length of Service used for frequence distribution and organised lowest to highest order in order to bring forth their mid-point.

Length of

Mid-point

frequence

Service

ten

degree Fahrenheit

fx

fx2

0-4

2

18

36

72

5-9

7

5

35

245

10-14

12

5

60

720

15-19

17

1

17

289

20-24

22

0

0

0

25-29

27

0

0

0

30-34

32

1

32

1024

amount

30

180

2350

mean

6.00

St.Dev.

6.51

Formulas used

The computation shows that the mean is 6.00 and the standard divergence is 6.51. The standard divergence measures the spread of the informations about the mean.

Drumhead Statisticss

Importance of Working Conditions allows to cipher drumhead statistics: mean, average, standard divergence, percentiles, etc.

Importanceof workingconditions

Mean

4.12

Standard Error

0.105089

Median

4.15

Manner

3.9

Standard Deviation

0.575596

Sample Variance

0.331310

Kurtosis

0.105686

Lopsidedness

-0.541828

Scope

2.3

Minimum

2.7

Maximum

5

Sum

123.6

Count

30

Assurance Level ( 95.0 % )

0.214931

The drumhead statistics show ;

  • The assurance interval ( 95.0 % ) is 4.12 ± 0.21.
  • Kurtosis and Skewness less than 2*0.105 ( standard mistake ) , so the information is normal. In this table Kurtosis 0.105 and Skewness -0.541 both are less than 2*0.105.

Undertaking 3 – t-test

T-test comparison satisfaction with working conditions for lasting and insouciant employees

Hydrogen0: There is no important difference Null Hypothesis

Hydrogen1: There is a important difference Alternative Hypothesis

Analysis and account

  • From the findings, the average satisfaction mark of the lasting employees is 3.8 and the average satisfaction mark of the causal employees is 3.9
  • The t-statistic is – 0.383 and the critical value is 2.048 for a two tailed trial.
  • Ignore the subtraction mark and since 0.383 & A ; lt ; 2.048, so Accept H0
  • Alternatively, since the p-value = 0.704 & A ; gt ; 0.05 so Accept H0
  • The sample grounds indicates that there is no important difference in the satisfaction mark of the lasting and insouciant employees at the 5 % degree of significance. The sample besides grounds indicates Null Hypothesis can non reject because P & A ; gt ; 0.05
Undertaking 4 – Correlation and Regression

Scatter graph compared tonss in correlativity of satisfaction and importance of working conditions

The spread graph shows positive correlativity at the 5 % degree, which means within these two variables there is a strong positive relationship. Arrested development used to find the quantitative relationship between two variables, and normally follows on from the constitution of important correlativity. The equation of the arrested development line is “y = a + bx” ; where a ( the intercept ) and B ( the incline ) are invariables.

Undertaking 5 – Written Analysis

Summary of findings:

  • In this assignment 30 employees record was collected from 363 population as a sample of informations analysis.
  • Datas used for multiple saloon chart comparing drawn between Employment position and Recommend of organisation which shows that 18 Employees who are Permanent and 6 who are Casual recommend yes. On the contrary, 4 Permanent and 2 Casual employees recommend no.
  • From graphical computations shows in a histogram that frequence distribution at 2.25 represent a category 0-3 for length of services of 30 employees. On the other manus, frequence distribution at 4.25 represent category 4 -4.5.
  • The drumhead statistics show that the assurance interval ( 95.0 % ) is 4.12 ± 0.21. Kurtosis and Skewness less than 2*0.105 ( standard mistake ) , so the information is normal. In this table Kurtosis 0.105 and Skewness -0.541 both are less than 2*0.105.
  • The average satisfaction mark of the lasting employees is 3.8 and the average satisfaction mark of the causal employees is 3.9. The t-statistic is – 0.383 and the critical value is 2.048 for a two tailed trial.
  • Ignore the subtraction mark and since 0.383 & A ; lt ; 2.048, so Accept H0
  • Alternatively, since the p-value = 0.704 & A ; gt ; 0.05 so Accept H0

The sample grounds indicates that there is no important difference in the satisfaction mark of the lasting and insouciant employees at the 5 % degree of significance.The sample besides grounds indicates Null Hypothesis can non reject because P & A ; gt ; 0.05

  • The spread graph shows positive correlativity at the 5 % degree, which means within these two variables there is a strong positive relationship. Arrested development used to find the quantitative relationship between two variables, and normally follows on from the constitution of important correlativity. The equation of the arrested development line is y = a + bx ; where a ( the intercept ) and B ( the incline ) are invariables

Appendix 1 – Copy of random figure tabular arraies used

375

183

106

366

240

74

62

121

179

153

174

229

308

175

38

80

307

54

46

196

275

152

388

359

54

272

267

76

348

84

234

17

335

380

266

276

192

311

180

50

333

194

149

147

311

383

25

62

82

337

284

185

351

68

328

68

57

297

223

211

279

343

383

258

258

36

359

75

376

23

83

117

345

85

276

350

148

315

395

62

104

380

238

304

20

15

240

115

25

353

229

29

216

139

153

64

294

55

192

117

35

324

374

335

74

330

195

342

63

139

378

301

109

270

184

214

47

177

124

173

41

18

145

398

79

248

333

101

44

90

38

132

21

139

371

144

304

100

247

2

176

259

138

226

245

245

292

77

382

368

372

348

18

201

394

3

48

394

306

348

95

360

312

205

61

351

130

316

262

334

396

193

144

294

57

390

179

145

35

346

199

117

16

276

374

203

188

335

319

388

76

127

157

96

57

299

170

244

157

279

183

95

87

378

338

310

154

197

391

163

37

101

31

333

358

65

113

343

31

105

86

338

21

135

196

325

298

284

159

188

387

301

62

397

320

19

109

162

376

347

212

33

46

60

51

66

26

197

147

112

156

132

249

259

62

229

212

305

293

344

389

66

370

245

22

329

92

152

249

14

RendomNumber( row )

Idaho

City

AgeGroup( old ages )

Length ofservice( old ages )

Employmentposition

Satisfaction ofWorkingconditions

Importanceof workingconditions

Recommendadministration as a good topographic point to work

183

279

metropolis 3

41-50

3

permanent

2.8

2.7

yes

106

156

metropolis 1

over 50

1

permanent

3.7

3.9

yes

240

362

metropolis 3

41-50

18

permanent

2.9

3.1

no

74

112

metropolis 2

over 50

14

insouciant

3.2

3.9

no

62

92

metropolis 2

41-50

3

insouciant

3.2

3.7

no

121

176

metropolis 1

over 50

13

permanent

2.4

4.3

yes

179

275

metropolis 3

over 50

9

permanent

3.4

4

yes

153

227

metropolis 2

41-50

2

insouciant

4.7

3.9

yes

174

270

metropolis 3

21-30

8

permanent

3.3

4.8

yes

229

349

metropolis 3

over 50

5

permanent

2.9

3.4

no

308

466

metropolis 8

31-40

5

permanent

3.7

3.5

yes

175

271

metropolis 3

31-40

4

permanent

2.9

4.2

no

38

63

metropolis 7

31-40

0

permanent

4.1

4.1

yes

80

118

metropolis 2

over 50

14

insouciant

4.4

4.5

yes

307

464

metropolis 8

41-50

3

permanent

4

4

yes

54

84

metropolis 5

31-40

3

permanent

4.2

4.2

yes

46

72

metropolis 5

Get instant access to
all materials

Become a Member
unlock