The Employee Satisfaction Scale - Essay Example

SOUTHLANDS COMPONENTS PLC Answer: The total of the satisfaction items (which is defined by the variable sat_total) for the employee satisfaction scale is computed as sum of all the 10 satisfaction scores and is given below: Variables n Mean SE(Mean) SD Skewness Kurtosis sat_total 102 42.99 1.345 13.59 -0.598 -0.418 The total of the commitment items (which is defined by the variable commit_tot) for the employee commitment scale is computed as sum of all the 10 commitment scores and is given below: Variables n Mean SE(Mean) SD Skewness Kurtosis commit_tot 102 37.01 1.334 13.47 0.055 -0.97 The descriptive (Means and SDs) for the employee satisfaction scale (individual is given below: Variables n Mean SE(Mean) SD Skewness Kurtosis sat1 102 4.14 0.155 1.57 -0.42 -0.96 sat2 102 4.21 0.163 1.64 -0.41 -1.15 sat3 101 4.09 0.168 1.69 -0.31 -1.26 sat4 102 4.42 0.162 1.63 -0.57 -1.03 sat5 102 4.15 0.160 1.62 -0.49 -0.96 sat6 102 4.58 0.149 1.51 -0.88 -0.29 sat7 101 4.32 0.166 1.67 -0.57 -1.05 sat8 101 4.74 0.139 1.40 -0.96 0.06 sat9 100 4.26 0.161 1.61 -0.57 -0.80 sat10 102 4.30 0.167 1.69 -0.57 -1.00 The reliability internal reliabilities (Cronbach’s Alpha) for the employee satisfaction is given below: Variable set No. of variables No. of valid cases Reliability Score Interpretation sat1 to sat10 10 98 (4 excluded) 0.953 Good The descriptive (Means and SDs) for the organizational commitment scale is given below: Variables n Mean SE(Mean) SD Skewness Kurtosis ocommit1 102 4.49 0.147 1.49 -0.45 -1.15 ocommit2 102 3.75 0.148 1.49 -0.08 -1.05 ocommit3 101 3.81 0.145 1.46 -0.10 -0.95 ocommit4 102 3.88 0.152 1.54 -0.20 -1.11 ocommit5 102 3.71 0.157 1.58 -0.02 -1.16 ocommit6 102 3.65 0.154 1.56 0.00 -1.04 ocommit7 102 3.53 0.147 1.48 0.20 -0.98 ocommit8 102 3.56 0.150 1.52 0.06 -1.08 ocommit9 102 3.61 0.156 1.58 -0.10 -1.07 ocommit10 102 3.06 0.159 1.61 0.35 -0.96 The reliability internal reliabilities (Cronbach’s Alpha) for the organizational commitment scale is given below: Variable set No. of variables No. of valid cases Reliability Score Interpretation ocommit1 to ocommit10 10 101 (1 excluded) 0.965 Good Note: Reliability for single item (either satisfaction total or commitment total) is incalculable (not able to be computed). 2A. Answer (7 Marks) Descriptives Variable Descriptive Statistics Statistic Std. Error initial_output Mean 2207.63 28.807 95% Confidence Interval for Mean Lower Bound 2150.43 Upper Bound 2264.83 5% Trimmed Mean 2204.04 Median 2195.00 Variance 78836.618 Std. Deviation 280.779 Minimum 1595 Maximum 3070 Range 1475 Interquartile Range 400 Skewness 0.253 0.247 Kurtosis -0.090 0.490 Extreme Values Variable Case Number Value initial_output Highest 1 58 3070 2 74 2740 3 98 2730 4 7 2700 5 61 2680 Lowest 1 3 1595 2 85 1670 3 55 1670 4 37 1760 5 89 1780 initial_output Stem-and-Leaf Plot  Frequency    Stem &  Leaf      1.00       15 .  9      2.00       16 .  77      3.00       17 .  689      7.00       18 .  0125779      8.00       19 .  12222568     15.00       20 .  001222333677889     12.00       21 .  334456777789     14.00       22 .  11112344557789      9.00       23 .  023556799      7.00       24 .  1246689      9.00       25 .  011224679      4.00       26 .  1248      3.00       27 .  034      1.00 Extremes    (>=3070)  Stem width:       100  Each leaf:       1 case(s) From the above histogram and box plots it is clear that case no.58 is an outlier because it falls outside the regular histogram and box plot. 1. By having a look at the Histogram and check the tails of distribution there is one are data points falling away as the extremes. 2. By inspecting the Boxplot to find whether SPSS identifies outliers, there is one outlier which is displayed as little circles with a case number attached (case number 58). 3. The outliers score is genuine and not an error. 4. Descriptive table provide you with an indication of how much a problem associated with these outlying cases. The expected value is the 5% trimmed Mean. SPSS removes the top and bottom 5 per cent of the cases and calculated a new mean value to obtain this Trimmed Mean value. If we compare the original mean and this new trimmed mean, we can see if the more extreme scores are having a lot of influence on the mean. If you find these two mean values are very different, you need to investigate the data points further. 5. The Extreme values table gives you with the highest and the lowest values recorded for that variable and also provide the ID of the person with that score. It helps to identify the case that has the outlying values. 2B. Answer: For this, we construct one sample t-test for single mean. The null hypothesis H0 is H0: The mean initial_output does not differ significantly from the national average 2300. ie.μ0=2300 against the alternative hypothesis H1, H1: The mean initial_output differ significantly from the national average 2300. ie.μ0#2300. Level of significance: 5% level or α=0.05. Test Statistic: to = , where s unbiased standard deviation x is sample mean and μ0=2300. by substituting the respective values in the formula we obtain the following results. One-Sample Statistics Variable n Mean SD SE(Mean) initial_output 95 2207.63 280.779 28.807 One-Sample Test Variable Test Value = 2300 t df Sig. (2-tailed) Mean Difference 95% Confidence Interval of the Difference initial_output -3.206 94 0.002 -92.368 -149.57 -35.17 Interpretation: From the above table, we observe that the mean difference of 92.368 between the sample mean (2207.63) and the population mean (2300) is highly significant (probability=0.002) even at 1% level. 3. Answer: When the initial_output and final_output is taken together for a study, we must examine whether there are outliers in both these variables, unlike there is only one outlier in initial_output so that we can omit both of those extreme cases coming out of initial_output and final_output for any further analysis (like correlations, regression etc..) so that the statistical analyses would be perfect. The following tables and diagrams depict the same. Variables Descriptives Statistic Std. Error initial_output Mean 2212.39 28.951 95% Confidence Interval for Mean Lower Bound 2154.86 Upper Bound 2269.91 5% Trimmed Mean 2206.91 Median 2205.00 Variance 75433.274 Std. Deviation 274.651 Minimum 1670 Maximum 3070 Range 1400 Interquartile Range 378 Skewness 0.338 0.254 Kurtosis -0.007 0.503 final_output Mean 2318.39 27.169 95% Confidence Interval for Mean Lower Bound 2264.41 Upper Bound 2372.37 5% Trimmed Mean 2315.93 Median 2325.00 Variance 66431.926 Std. Deviation 257.744 Minimum 1730 Maximum 3185 Range 1455 Interquartile Range 380 Skewness 0.260 0.254 Kurtosis 0.467 0.503 Extreme Values Variables No. Case Number partnum Value initial_output Highest 1 58 58 3070 2 74 74 2740 3 98 98 2730 4 7 7 2700 5 61 61 2680 Lowest 1 85 85 1670 2 55 55 1670 3 37 37 1760 4 89 89 1780 5 81 81 1790 final_output Highest 1 58 58 3185 2 61 61 2900 3 27 27 2705 4 54 54 2705 5 7 7 2695a Lowest 1 55 55 1730 2 99 99 1765 3 37 37 1875 4 10 10 1885 5 78 78 1935 a. Only a partial list of cases with the value 2695 are shown in the table of upper extremes. initial_output Stem-and-Leaf Plot  Frequency    Stem &  Leaf      2.00       16 .  77      3.00       17 .  689      7.00       18 .  0125779      7.00       19 .  1222568     14.00       20 .  00122233677889     12.00       21 .  334456777789     14.00       22 .  11112344557789      9.00       23 .  023556799      7.00       24 .  1246689      7.00       25 .  0122679      4.00       26 .  1248      3.00       27 .  034      1.00 Extremes    (>=3070)  Stem width:       100  Each leaf:       1 case(s) final_output Stem-and-Leaf Plot  Frequency    Stem &  Leaf      2.00       17 .  36      2.00       18 .  78      6.00       19 .  356677      8.00       20 .  13355799     12.00       21 .  122224566799     12.00       22 .  002233566689     15.00       23 .  112233466667899     10.00       24 .  1133346779      9.00       25 .  001157788     10.00       26 .  0013334599      2.00       27 .  00       .00       28 .      1.00       29 .  0      1.00 Extremes    (>=3185)  Stem width:       100  Each leaf:       1 case(s) Interpretation: Now by analysing the final_input and final_output variables together, we observe that only case number 58 is the outlier, shown in both the initial_output and final_output box plots. So we can omit that entry for analysis involving the variables initial_output and final_output. 3B. Answer Paired Samples Statistics Variables Mean n Std. Deviation Std. Error Mean initial_output 2212.39 90 274.651 28.951 final_output 2318.39 90 257.744 27.169 Paired Samples Correlations Variables n Correlation Sig. Pair initial_output & final_output 90 0.880** 0.000 The correlation between initial_output and final_output is 0.880 and is highly significant at 5% level and 1% level. Paired Samples Test Variables Paired Differences t df Sig. (2-tailed) Mean SD SE(Mean) 95% Confidence Interval of the Difference Lower Upper initial_output - final_output -106.000 131.21 13.831 -133.48 -78.52 -7.664 89 0.000 Interpretation: From the above t-table, we observe that there is a significant difference between the initial_output and final_output (t value is significant with probability 0.000) which indicates that the training programme is effective. 4A. Answer Descriptives Variables gender Statistic Std. Error sat_total Female Mean 42.76 1.966 95% Confidence Interval for Mean Lower Bound 38.81 Upper Bound 46.71 5% Trimmed Mean 43.54 Median 43.50 Variance 193.207 Std. Deviation 13.900 Minimum 9 Maximum 60 Range 51 Interquartile Range 20 Skewness -.639 .337 Kurtosis -.345 .662 Male Mean 43.21 1.860 95% Confidence Interval for Mean Lower Bound 39.48 Upper Bound 46.94 5% Trimmed Mean 44.00 Median 46.00 Variance 179.817 Std. Deviation 13.410 Minimum 10 Maximum 60 Range 50 Interquartile Range 23 Skewness -.570 .330 Kurtosis -.429 .650 sat_total Stem-and-Leaf Plot for gender= Female  Frequency    Stem &  Leaf      1.00        0 .  9      1.00        1 .  0      1.00        1 .  9      3.00        2 .  003      4.00        2 .  7777      3.00        3 .  334      6.00        3 .  778899      6.00        4 .  001222      5.00        4 .  56789      8.00        5 .  11111334      6.00        5 .  577889      6.00        6 .  000000  Stem width:        10  Each leaf:       1 case(s) sat_total Stem-and-Leaf Plot for gender= Male  Frequency    Stem &  Leaf      2.00        1 .  00      6.00        2 .  056799     11.00        3 .  00022223677     12.00        4 .  000134667778     17.00        5 .  11334444556789999      4.00        6 .  0000  Stem width:        10  Each leaf:       1 case(s) 4B.Answer Group Statistics gender N Mean SD SE(Mean) sat_total Male 52 43.21 13.410 1.860 Female 50 42.76 13.900 1.966 Independent Samples Test Levenes Test for Equality of Variances t-test for Equality of Means Variable F Sig. t df Sig. (2-tailed) Mean diff. SE(diff.) sat_total 0.000 0.993 0.167 100 0.868 0.452 2.704 Interpretation: From the above table, it is observed that there is no significant difference between males and females with regard to total satisfaction score. 5A. Answer Descriptive Statistics of final output training groupwise training_condition Statistic Std. Error final_output None Mean 2254.35 40.879 95% Confidence Interval for Mean Lower Bound 2170.87 Upper Bound 2337.84 5% Trimmed Mean 2256.68 Median 2255.00 Variance 51802.903 Std. Deviation 227.603 Minimum 1765 Maximum 2645 Range 880 Interquartile Range 320 Skewness -.023 .421 Kurtosis -.596 .821 1 Day Mean 2237.03 43.077 95% Confidence Interval for Mean Lower Bound 2149.18 Upper Bound 2324.89 5% Trimmed Mean 2236.18 Median 2180.00 Variance 59378.805 Std. Deviation 243.678 Minimum 1730 Maximum 2705 Range 975 Interquartile Range 345 Skewness .273 .414 Kurtosis -.450 .809 1 Week Mean 2427.73 46.925 95% Confidence Interval for Mean Lower Bound 2332.14 Upper Bound 2523.31 5% Trimmed Mean 2427.48 Median 2435.00 Variance 72665.767 Std. Deviation 269.566 Minimum 1730 Maximum 3185 Range 1455 Interquartile Range 275 Skewness .028 .409 Kurtosis 2.036 .798 final_output Stem-and-Leaf Plot for training_condition= None  Frequency    Stem &  Leaf      1.00       17 .  6       .00       18 .      4.00       19 .  3677      4.00       20 .  3579      3.00       21 .  267      6.00       22 .  223566      6.00       23 .  266789      2.00       24 .  37      2.00       25 .  58      3.00       26 .  134  Stem width:       100  Each leaf:       1 case(s) final_output Stem-and-Leaf Plot for training_condition= 1 Day  Frequency    Stem &  Leaf      1.00       17 .  3      1.00       18 .  8      2.00       19 .  56      5.00       20 .  13359      8.00       21 .  12223569      3.00       22 .  069      4.00       23 .  3389      3.00       24 .  179      1.00       25 .  0      3.00       26 .  059      1.00       27 .  0  Stem width:       100  Each leaf:       1 case(s) final_output Stem-and-Leaf Plot for training_condition= 1 Week  Frequency    Stem &  Leaf      2.00 Extremes    (==3185)  Stem width:       100  Each leaf:       1 case(s) Interpretation From the above box plot, it is observed that the final output of the case number 58 is outlier, which indicates that in one weeks training programme, the output of case number 58 has tremendously improved in one week training programme compared to the other respondents. Also we notice that case numbers 37 and 55 are extreme low outliers in 1 week training programme. There is no effect of training programme for these outliers. 5B.Answer: final_output n Mean Std. Deviation Std. Error Minimum Maximum None 31 2254.35 227.603 40.879 1765 2645 1 Day 32 2237.03 243.678 43.077 1730 2705 1 Week 33 2427.73 269.566 46.925 1730 3185 Total 96 2308.18 260.436 26.581 1730 3185 ANOVA of final output by no. of days Source of variation Sum of Squares df Mean Square F Between Groups 723421.379 2 361710.689 5.881 Within Groups 5720134.611 93 61506.824 Total 6443555.990 95 Dependent Variable:final_output (i) training_condition (j) training_condition Mean Difference (i-j) Std. Error Sig. Tukey HSD None 1 Day 17.324 62.499 0.959 1 Week -173.372* 62.032 0.017* 1 Day 1 Week -190.696* 61.530 0.007** *. The mean difference is significant at the 0.05 level. Homogeneous Subsets final_output training_condition n Subset for alpha = 0.05 1 2 Tukey HSDa 1 Day 32 2237.03 None 31 2254.35 1 Week 33 2427.73 Sig. .958 1.000 Means for groups in homogeneous subsets are displayed. a. Uses Harmonic Mean Sample Size = 31.979. Interpretation: From the above output, we observe that the final output of 1 week training programme is tremendously appreciable when compared to other training conditions ie. 1 day training programme or no training programme. The homogeneous subsets indicate that there is a significant difference between the 1 day and 1 week training programmes but there is no significant difference in the final output between 1 day and no training programme. 6A. Answer For sake of convenience we categorize the years served into three 1. Upto 5 years is recoded as 1, from 6 to 10 years is recoded as 2 and above 10 is recoded as 3. Descriptives Years Served Statistic Std. Error sat_total 0-5 Mean 44.45 2.036 95% Confidence Interval for Mean Lower Bound 40.36 Upper Bound 48.54 5% Trimmed Mean 45.52 Median 49.00 Variance 211.413 Std. Deviation 14.540 Minimum 9 Maximum 60 Range 51 Interquartile Range 21 Skewness -.893 .333 Kurtosis -.005 .656 6-10 Mean 42.67 1.931 95% Confidence Interval for Mean Lower Bound 38.76 Upper Bound 46.58 5% Trimmed Mean 43.11 Median 44.00 Variance 145.439 Std. Deviation 12.060 Minimum 10 Maximum 60 Range 50 Interquartile Range 22 Skewness -.500 .378 Kurtosis -.312 .741 11-15 Mean 37.83 4.002 95% Confidence Interval for Mean Lower Bound 29.03 Upper Bound 46.64 5% Trimmed Mean 37.59 Median 37.50 Variance 192.152 Std. Deviation 13.862 Minimum 20 Maximum 60 Range 40 Interquartile Range 23 Skewness .332 .637 Kurtosis -.817 1.232 commit_total 0-5 Mean 35.92 1.895 95% Confidence Interval for Mean Lower Bound 32.11 Upper Bound 39.73 5% Trimmed Mean 35.89 Median 39.00 Variance 183.194 Std. Deviation 13.535 Minimum 9 Maximum 60 Range 51 Interquartile Range 22 Skewness .064 .333 Kurtosis -.845 .656 6-10 Mean 39.26 2.084 95% Confidence Interval for Mean Lower Bound 35.04 Upper Bound 43.47 5% Trimmed Mean 39.42 Median 39.00 Variance 169.354 Std. Deviation 13.014 Minimum 15 Maximum 60 Range 45 Interquartile Range 20 Skewness -.007 .378 Kurtosis -.927 .741 11-15 Mean 34.33 4.249 95% Confidence Interval for Mean Lower Bound 24.98 Upper Bound 43.68 5% Trimmed Mean 33.93 Median 33.00 Variance 216.606 Std. Deviation 14.718 Minimum 17 Maximum 59 Range 42 Interquartile Range 29 Skewness .397 .637 Kurtosis -1.377 1.232 commit_total Stem-and-Leaf Plots commit_total Stem-and-Leaf Plot for yearserved= 0-5  Frequency    Stem &  Leaf      1.00        0 .  9      4.00        1 .  4669     13.00        2 .  0011122245699     12.00        3 .  004567799999     11.00        4 .  00012233446      7.00        5 .  0123579      3.00        6 .  000  Stem width:        10  Each leaf:       1 case(s) commit_total Stem-and-Leaf Plot for yearserved= 6-10  Frequency    Stem &  Leaf       .00        1 .      3.00        1 .  568      2.00        2 .  13      4.00        2 .  6699      6.00        3 .  001233      6.00        3 .  556799      4.00        4 .  1112      1.00        4 .  6      7.00        5 .  0000113      2.00        5 .  57      4.00        6 .  0000  Stem width:        10  Each leaf:       1 case(s) commit_total Stem-and-Leaf Plot for yearserved= 11-15  Frequency    Stem &  Leaf      2.00        1 .  79      3.00        2 .  014      3.00        3 .  336      2.00        4 .  99      2.00        5 .  29  Stem width:        10  Each leaf:       1 case(s) sat_total Stem-and-Leaf Plots sat_total Stem-and-Leaf Plot for yearserved= 0-5  Frequency    Stem &  Leaf      1.00        0 .  9      3.00        1 .  009      4.00        2 .  0677      9.00        3 .  023477889      9.00        4 .  001225679     19.00        5 .  1111333445678889999      6.00        6 .  000000  Stem width:        10  Each leaf:       1 case(s) sat_total Stem-and-Leaf Plot for yearserved= 6-10  Frequency    Stem &  Leaf      1.00        1 .  0       .00        1 .       .00        2 .      6.00        2 .  577799      5.00        3 .  02233      2.00        3 .  77      6.00        4 .  001234      5.00        4 .  67778      7.00        5 .  1113444      5.00        5 .  55779      2.00        6 .  00  Stem width:        10  Each leaf:       1 case(s) sat_total Stem-and-Leaf Plot for yearserved= 11-15  Frequency    Stem &  Leaf      3.00        2 .  003      4.00        3 .  0269      3.00        4 .  068       .00        5 .      2.00        6 .  00  Stem width:        10  Each leaf:       1 case(s) We observe that there are no outliers. 6B. Answer Correlations yrsserv sat_total commit_total yrsserv Pearson Correlation 1 -.084 .053 Sig. (2-tailed) .400 .598 N 102 102 102 sat_total Pearson Correlation -.084 1 .618** Sig. (2-tailed) .400 .000 N 102 102 102 commit_total Pearson Correlation .053 .618** 1 Sig. (2-tailed) .598 .000 N 102 102 102 **. Correlation is significant at the 0.01 level (2-tailed). From the above table we observe that there exists significant relationship between total satisfaction score and total commitment score. There is no significant relationship between years served and satisfaction total or 6C. Answers Refer to 6b and the results displayed. Correlations yrsserv sat_total commit_total yrsserv Pearson Correlation 1 -.084 .053 Sig. (2-tailed) .400 .598 N 102 102 102 sat_total Pearson Correlation -.084 1 .618** Sig. (2-tailed) .400 .000 N 102 102 102 commit_total Pearson Correlation .053 .618** 1 Sig. (2-tailed) .598 .000 N 102 102 102 **. Correlation is significant at the 0.01 level (2-tailed). Interpretation: From the above table we observe that there exists significant relationship between total satisfaction score and total commitment score. There is no significant relationship between years served and satisfaction total or commitment total. 6D. Answers Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .627a .393 .381 10.595 a. Predictors: (Constant), sat_total, yrsserv ANOVA Model Sum of Squares df Mean Square F Sig. Regression 7208.563 2 3604.282 32.110 .000a Residual 11112.427 99 112.247 Total 18320.990 101 a. Predictors: (Constant), sat_total, yrsserv b. Dependent Variable: commit_total Coefficients Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 7.899 4.053 1.949 .054 yrsserv .411 .305 .106 1.346 .181 sat_total .622 .078 .627 7.985 .000 a. Dependent Variable: commit_total Interpretation From the above regression table we observe that the year served is not influential in deciding total commitment score (probability of significance 0.181>0.05) while the total satisfaction score is highly influential in deciding organizational commitment score (probability of significance 0.0000.05). 7. Answer The test used is independent t test. Group Statistics Variables Gender n Mean SD SE(Mean) initial_output Male 46 2199.78 320.217 47.213 Female 49 2215.00 241.130 34.447 final_output Male 48 2286.15 276.952 39.975 Female 48 2330.21 243.728 35.179 Independent Samples Test Variables Levenes Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference initial_output 3.220 0.076 -0.263 93 0.793 -15.217 57.931 final_output 0.378 0.540 -0.827 94 0.410 -44.062 53.250 Interpretation: From the above table we observe that there is no significant difference between gender in initial output (probability 0.793>0.05) and also in final output (probability 0.41>0.05). Both males and females are equally distributed with regard to initial output and final output mean scores. Read More