# Survey of Employee Satisfaction Essay

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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.

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 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