Create a business plan that you will present to a senior manager at a law firm.
The report should be informative, but not too concise. It should also follow a structured structure that is easy to read and understand.
Draw a random sample for statistical analysis.
* Enhance and develop computing skills, focusing on the use built-in functions of MS Excel and MS Word
* Apply statistical techniques for a data set
Certain initiatives were put in place to foster a more nurturing and empowering work environment.
From the above population, a 100-member sample was taken.
The firm employed 100 employees to conduct statistical tests to see if the results have been achieved.
The report also discusses the nature and extent to which social media usage is associated with productivity and job satisfaction.
A regression analysis between these variables is also done.
While the majority of sample employees are female, the representation is almost equal for both genders. This indicates that the firm has high quality gender workers.
The average age of employees in this firm is well above 40. This can also be seen in the histogram which shows the majority of employees are in the 30-60 years bracket.
This is normal for law firms where skills improve over time.
It is not balanced on the right, with most employees spending less time on social networks.
There are very few employees who appear to be addicted.
It is not uncommon for data to be scattered.
Time on SM
Most employees are productive for 25 hours.
But, half of the employees work in productivity levels below 16 hours.
Further, although the potential range of values is impressive, the overall deviation from the norm is small.
It is alarming that more than a quarter of the sample employees express low satisfaction. This indicates that proactive changes are needed.
But, only 25% of employees feel satisfied with their company. This indicates that some adjustments are needed on the part of the firm in order to increase overall satisfaction.
Employees at the firm have low stress levels, with only about 65% reporting a level below three.
It is remarkable that only two employees have stress levels greater than 5.
Peer support seems moderate for most employees, as the highest responses tend to be concentrated here.
Some employees are stuck at the bottom end of this scale, so it is necessary to take the appropriate steps to improve the peer support.
With 95% confidence, we can conclude that the population average age for all employees would be in the range 38.99 years to 43.95.
The population data also show that the true population average for the variable is 42.36, which places it in the range shown above (Eriksson, Kovalainen (2015)).
It is possible to conclude that the average time spent on social media by all employees in the interval (0.05 hour,1.42 hour) with a confidence level of 95%.
The population data also shows that the true population mean is 1.17 hours. This position falls between the intervals shown above (Flick 2015).
Hypothesis testing was performed to prove that female employees spend a greater amount of time on social networking than their male counterparts.
Type of Hypothesis : Upper Tail, Test statistic : T (-0.29). P value : 0.39. Degree of Freedom : 92
Decision: The sample data doesn’t support the above claim (Hair, et.
Hypothesis Testing was done to prove that stress levels post-improvement in the company’s employee environment is lower than pre-stress.
Type of Hypothesis : Lower Tail, Test statistic : T (-5.61), P value : 0.00, Degree Freedom : 99
Decision: The sample evidence supports the above claim (Flick (2015)).
Hypothesis Testing was done to prove that the level of peer support after the positive change in the workplace environment has increased by the firm has higher than before.
Type of Hypothesis : Upper Tail, Test statistic : T (3.52) P value : 0.00 Degree of Freedom : 99
Decision: The sample evidence supports the above claim (Hillier (2006)).
Visually, it is clear that the pattern is linear and has a negative or downward slope. This can be seen in the sample data.
A correlation coefficient of 0.93 indicates that there is a strong negative relation between the variables. This is in line with expectations (Hillier (2006)).
The dependent variable (i.e.
The dependent variable, i.e. productivity, is often negatively affected when employees increase their time on social networking which acts as an independent variable.
R2 is extremely high so 86% of productivity changes are accounted.
The productivity of a person who spends an hour on social media would drop to 5.6 hours (Flick (2015)).
The attached shows that the slope of this regression model is statistically significant.
Below you will see the required scatterplot with social media time as an independent variable and the dependent variables, such as job satisfaction.
The scattered distribution makes the correlation seem low, which is supported by low values of the correlation coefficient (Eriksson, Kovalainen (2015)).
Negative slope indicates that the relationship between the variables is negative. It means that the social media use increases, but the job satisfaction tends towards decreasing.
The regression model and slope coefficient are not significant, as well as the coefficient of determination which is very low. This supports the conclusion by Hair et.
This discussion shows that the new initiatives taken by the law office to improve the work environment for employees have yielded rich dividends. The stress level and the level of peer support have decreased and increased respectively, in comparison to their previous levels.
Additionally, the hours spent on Facebook and underlying productivity have a strong negative relationship.
But, this is not true for employee satisfaction. This has a very weak relationship with social media hours.
Given that confidence intervals used to calculate population mean from sample data were derived using the actual population means, this implies that these two variables are represented values.
A major drawback is the possibility that the random sample might not be representative of all the variables. This may lead to an incorrect conclusion.
Eriksson, P., and Kovalainen A.
(3). Quantitative methods of business research, 3rd edition, London: Sage Publications.
The introduction to research methodology: An easy guide for beginning researchers, 4th ed. New York: Sage Publications.
Hair, J. F. Wolfinbarger M. Money, A. H. Samouel P., Page M. J.
New York: Routledge.
Hillier F. (2006). Introduction to Operations Research. New York: McGraw Hill Publications.