THINKING ABOUT THE BALANCE BETWEEN WORK AND PRIVATE LIFE
Introduction
The goal of this paper is to present the analysis of the data gathered from the respondents. The main objective of this research is to identify if there is a significant relationship in the balance between work and private life through different variables. For this report, descriptive analysis, correlation analysis and factor analysis will be considered.
Assignment 1 Descriptive Statistics
· Demographic Profile
Table 1
The table above presents the descriptive statistics of the demographic profiles of the collected data. The tables and graphs below provide the frequency analysis of the demographic profiles of the respondents.
Table 2
The table above presents that employment status of the respondents. Herein, it shows that majority of the respondents are employees with 83% out of 285 while 13.3% of them are self-employed.
Table 3
The table above presents that employment pattern of the respondents. Herein, it shows that majority of the respondents are full time employees with 89.1% out of 284 while only 10.5% were part time employees.
Table 4
The table above presents that number of years in service of the respondents. As can be seen 26.3% out of 283 respondents were working for more than 8 years while 21.8% are working for 3-5 years. This is shown that majority of the respondents have long-term relations with their job.
Table 5
The table above presents the current working company of the respondents. 34.4% of the respondents are working in local government and 18.6% are working in government department. Some 17.5% and 17.2% were working in their own business and private company.
Table 6
In terms of age, it can be said that based on the table above 30.9% of the respondent belongs to 36-45 years and 27.1% belongs to 27.1% indicating that majority of the respondents were young adults.
Table 7
Based on the data provided, it is said that 50.9% of the total respondents were female while only 49.1 percent were male, indicating that women are willing to answer survey questionnaire.
Table 8
The table above presents the educational background of the respondents showing that majority of them graduated from a university.
Table 9
Table 10
In terms of seniority in the workplace, 48.4% of the total respondents belong to middle level followed by 36.8% as seniors. This further indicates their years in the service.
The table above presents the status of the income of the respondents which shows that 43.9% perceived that they have the same equity and 23.% have a bit less income than the others.
The tables below will provide the analysis of the answers of the respondents in terms of clustered bar chart and/or pie chart
The following table will show the data analysis of the answers of the respondents through clustered bar chart, pie chart
· Analysis: Work Life Balance Direct Measures
A01 = “I am happy with my personal work/life balance.”
The bar graph shows that majority of the respondents are happy with their personal work/life balance.
A02 = “It is difficult for me to get the right balance.”
In the table above, it shows that most of the respondents are semi-definite in their perception on the difficulty of getting the right balance.
A03 = “It is important that I get the balance right. “
In the table above, it shows that majority of the respondents definitely believe that it is important to get the balance right.
A04= “It is hard to get quality time with family and friends”
Most of the respondents are definite that it is hard to get quality time with family and friend while working as seen in the table above.
· PERSONAL ATTITUDES TO WORK
A05 = “Work always comes first for me.”
A06 = “If I didn’t need the money, I would leave tomorrow.”
A07 = “I think this is a pretty good place to work.”
A08 = “There’s not much I would want to change about my job.”
How important is ‘work/life balance’ for you? What would be your ideal work life balance?
Organisational Policies and Managerial Attitudes to technology and WLB
ORGANISATIONAL POLICIES to WLB
C01 = “I am allowed to do personal activities in work time in return for working in private time.”
C02 = “My organisation provides me with the right IT and support.”
C03 = “My company’s policies encourage flexible working.”
C04 = “I am mostly able to decide where I do my work.”
§ MANAGERIAL ATTITUDES TO WLB
C05 = “I am expected to use IT to work in private time.”
C06 = “In this job you are expected to work over 40 hrs a week.”
· PERSONAL ATTITUDES TO TECHNOLOGY
·
C07 = “I object to the way IT brings work into private time.”
C08 = “I need to be able to switch off and get away from work.”
· AUTONOMY
C09 = “I am mostly able to decide when I do my work.”
C10 = “I am happy to make important work decisions on my own.”
C11 = “My manager trusts me to work effectively from home.”
C12 = “At home I have all the technology I need for work.”
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What is the major impediment to you having your ideal ‘work/life balance’ right now? What would you like done to improve your personal work life balance?
· Self Management and technology
Self management of technology across work/life boundaries
M02 = “I am effective in managing the IT available to me.”
M03 = “I choose to use IT that lets me work away from the office.”
M04 = “I think IT blurs the boundary between home and work.”
SELF MANAGEMENT
M05 = “I am good at managing my own time and output.”
M06 = “I think I have the right work/life balance now.”
M07 = “I often access company networks or email from home.”
M08 = “I use work IT in my own time and for personal use.”
ATTITUDES TO IT
M09 = “I am comfortable and competent with computers & IT.”
M10 = “It is easy to do more of my job at home now due to IT”
What effect have these technologies had on your personal work/life balance?
Very Negative 1 – - – - – - – - – - – - – - – – - – - – - 5 Very Positive
E01 = “Cellphones”
E02 = “Laptops”
E03 = “PDAs”
E04 = “Internet access “
E05 = “Broadband at home”
E06 = “Home office”
E07 = “Wireless connectivity”
E08 = “Remote access to job databases”
E09 = “Remote access to job intranet”
3. Histogram with Normal Curve of Demographics
Employment Status
Employment Pattern
Length of Service
Type of organization
Age
Gender
Education
Seniority
Equity
4. Scatter Diagram
The table below shows the scatter diagram for the work/life attitude of the respondents with their personal attitude.
6. Chi Squared
Chi-square is a family of distributions that vary with degrees of freedom (a concept that will be discussed at length later on). But in general, as the degrees of freedom become infinitely large, chi square approaches normality. Note: the expected value of each chi square distribution (mean) is equal to the number of degrees of freedom for that curve.
This is used to determine the relationship between two variables that are set have relationship. The formula for this is as follows:
χ2 =
where : χ2 = chi-square value
oi = observe frequency
ei = expected frequency
in this report chi-square analysis will be conducted to the work life balance and personal attitude of the respondents.
Based on the result above, contains the output of the Chi-Square test. Df equals the number of categories minus one. In this regard, the sample has 4 categories (work life balance, personal attitude, organizational policies and managerial attitude. Small significance values (<.05) indicate that the observed distribution does not conform to the hypothesized distribution. In this the significant level is less than .05 which is .000. In this regard, it can be concluded that based on the chi-squared, the distribution of respondents with regards to this categories differs from the hypothesized distribution.
Assignment 2: Correlation
To be able to determine if there is a correlation between the assessments of the two groups of respondents the Pearson’s Coefficient of Correlation was used.
Correlation is a measure of degree of relationship between paired data. All statistical research aim to establish relationship between paired variables so as to enable the researcher to predict one variable in terms of the other variable. For example, the weighted mean of the responses of the beginners class tend to be related to the weighted mean of responses of the teachers.
The formula for Pearson’s Coefficient of Correlation:
N SXY – SXSY
r =
[NSX - (SC)2][NSY - (SY)2]
0.00 to 0.20
Negligible correlation
0.21 to 0.40
Low correlation
0.41 to 0.50
Substantial correlation
0.51 to 0.80
Marked correlation
0.81 to 1.00
High to very high correlation
The researcher tries to determine the relationship between the price, facilities and services of a certain hotel with respect to hotel differentiation. The computation and illustration of scatter plot was presented below:
The statistics above shows the relationship of work/life balance and personal attitude of the respondents. The computed correlation value of 0.066 indicates a marked correlation between paired variables. Meaning to say, the relationship of work life balance and personal attitude of the respondents are interpreted as marked correlation.
To see another correlation, work/life measure will be tested for correlation in the organizational policies and managerial attitude as perceived by the respondents.
Based on the data analyzed, the computer correlation value as presented above is -.119 which indicates that work/life balance of the respondents has negligible correlation with the organisational policies.
In line with the correlation of the work/life balance and managerial attitude as perceived by the respondents, the value is .004 indicating that these variables have negligible correlation.
In line with the correlation of the work/life balance with the personal attitude of the respondents with regards to technology, the value is .122 indicating that there is a negligible correlation between the two variables.
Third Assignment : Regression analysis
When there is a general linear relation between two variables X and Y, it is possible to construct a linear equation that allows to predict the Y value corresponding to any known value of X. The regression equation can be used to compute a predicted Y value for any value of X. The accuracy of the prediction is measured by the standard error of estimate which provides a measure of the average distance (or error) between the predicted Y value on the line and the actual data point.
This table displays R, R squared, adjusted R squared, and the standard error. R, the multiple correlation coefficients, is the correlation between the observed and predicted values of the dependent variable. The values of R for models, produced by the regression procedures, range from 0 to 1. Larger values of R indicate stronger relationships. R squared is the proportion of variation in the dependent variable explained by the regression model. The values of R squared range from 0 to 1. Small values indicate that the model does not fit the data well. The sample R squared tends to optimistically estimate how well the models fits the population. Adjusted R squared attempts to correct R squared to more closely reflect the goodness of fit of the model in the population. Use R Squared to help you determine which model is best. In this regard, with the R squared (.051), it shows that the variables does not fit the data well.
This table summarizes the results of an analysis of variance. The sum of squares, degrees of freedom, and mean square are displayed for two sources of variation, regression and residual. The output for Regression displays information about the variation accounted for by your model. The output for Residual displays information about the variation that is not accounted for by your model. And the output for Total is the sum of the information for Regression and Residual. A model with a large regression sum of squares in comparison to the residual sum of squares indicates that the model accounts for most of variation in the dependent variable. Very high residual sum of squares indicate that the model fails to explain a lot of the variation in the dependent variable, and you may want to look for additional factors that help account for a higher proportion of the variation in the dependent variable. The mean square is the sum of squares divided by the degrees of freedom. The F statistic is the regression mean square (MSR) divided by the residual mean square (MSE). The regression degrees of freedom is the numerator df and the residual degrees of freedom is the denominator df for the F statistic. The total number of degrees of freedom is the number of cases minus 1. If the significance value of the F statistic is small (smaller than say 0.05) then the independent variables do a good job explaining the variation in the dependent variable. If the significance value of F is larger than say 0.05 then the independent variables do not explain the variation in the dependent variable. In this regard having, .073 significant value which is larger than .05 means that the independent variable (wok/life balance measure) do not explain the variation in the dependent variables (personal attitude, organizational policies, managerial attitude, personal attitude towards technology, autonomy, self management and technology and attitude to technology).
The unstandardized coefficients are the coefficients of the estimated regression model. In this report the estimated model is work/life balance which is 2.372, personal attitude with 7.922, organizational policies with -3.54, managerial attitude of -9.17, personal attitude towards technology 4.806, autonomy -2.07, self management and technology 6.77 and attitude to it -6.50. Often the independent variables are measures in different units. The standardized coefficients or betas are an attempt to make the regression the regression analysis, you would get the beta coefficients as your unstandardized coefficients. The t statistics can help you determine the relative importance of each variable in the mode. As a guide regarding useful predictors, look for t values well below -2 or above +2. Based on the analysis it shows that
Credit:ivythesis.typepad.com
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