Physical Activity and Employees’ Productivity

Strategies and approaches to improve employees’ productivity are actively discussed in the business environment. That is why much attention is paid to discussing differences in the productivity of those persons who are physically active and those who follow the sedentary lifestyle. In order to discuss these differences in detail and with the help of statistical analysis, it is necessary to formulate the answer to the following research question: Does the increase in physical activity improve employees’ productivity?

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The question can be answered with the help of a one-way ANOVA based on independent samples because it is necessary to state how employees with the high physical activity level can differ from the other employees in relation to the aspect of productivity. A one-way ANOVA can be effectively applied to the research question because it provides opportunities to determine differences between means (Huck, 2012, p. 129). In this case, numerical differences become obvious while discussing the productivity of employees. The research is focused on testing the following hypotheses:

H0: µ¹ = µ² = µ³ where H0: There are no differences in the productivity of the employees characterized by different levels of physical activity.

H1: µ¹ ≠µ² ≠µ³ where H1: The increase in physical activity improves the employees’ productivity.

While discussing the research question, it is important to note that the focus on four levels of physical activity as an independent variable is important to conclude about differences in the employees’ productivity. Moreover, Type I errors are reduced, and Type II errors are more typical for this research conducted with the help of the one-way ANOVA.


The participants of the survey are 120 males and females, where the male population composes 75%, and the female population is presented by 25%. The one-way ANOVA, as the used statistical test, is based on independent samples. The participants were selected according to the convenience sampling principle with the focus on employees working at different positions in many companies in such industries as retailing, healthcare, and finance. Referring to demographic characteristics, it is important to note that the participants are males and females aged 21-45. The participants are characterized by a diverse ethnic background. Thus, the sample population is rather representative, and it is expected to present employees of different ages and to work in different spheres.

While focusing on the procedures, it is important to discuss the used variables. The independent variable is the physical activity of employees, which is noted by the participants in categories used to determine their levels of physical activity. Focusing on the operational definition, it is important to note that physical activity is the level of the employees’ involvement in performing different physical exercises.

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Different levels of physical activity are categorized according to the subjective vision of employees in such four groups as the sedentary lifestyle, low physical activity, moderate physical activity, and high physical activity. Thus, the variable is qualitative, and it is measured according to the nominal scale in levels, “sedentary,” “low,” “moderate,” and “high.”

The dependent variable is productivity, which is demonstrated by employees during their working hours. The operational definition of productivity is the number of hours spent on performing a concrete task effectively. Thus, the productivity of the participants is measured in hours spent on performing a list of tasks that are similar in their nature while discussing the specifics of different industries. The tasks are affirmed by managers, and the number of hours is noted by both managers and performers. The variable is continuous, and it is measured in a number of hours according to the ratio scale.


The statistical test which should be used to conduct the research is a one-way ANOVA that is based on independent samples. A one-way ANOVA provides researchers with many opportunities to focus on differences between means and to state the effects and aspects of the interaction. The test was chosen because it can clearly determine the presence of differences in means discussed in relation to various categories.

That is why the test is appropriate for the research because it demonstrates the presence of differences in the productivity of different groups of employees and accentuates the effect of physical activity on productivity. However, to interpret the results of ANOVAs effectively, it is necessary to use posthoc tests because ANOVA focuses on the presence of differences and effects without determining which means are actually different.

The information obtained from the results of ANOVA and posthoc tests will be the numerical data and the coefficient of differences in productivity characteristics for the employees living a different lifestyle. The changes in the coefficient will be interpreted with the help of post-hoc tests in order to state which concrete factors and means influence the observed differences. In order to draw conclusions on the hypotheses, it is necessary to focus on comparing the coefficients and determine the highest ones in relation to the observed productivity. Much attention should be paid to comparing the results with the expected average performance or productivity. Any differences in the expected numbers will be discussed in detail to draw conclusions.


The expected faults associated with the research are connected with the data collection and interpretation of the results. Thus, employees can determine the level of their physical activity inadequately. Furthermore, the number of hours spent to perform tasks can be fixed inaccurately. The interpretation of results can be challenged with difficulties associated with the use of the one-way ANOVA and posthoc tests (American Psychological Association, 2010, p. 12). Possible biases associated with the employees’ job positions and experience should be avoided while recording and interpreting results. Such assumptions as the connection between high physical activity and productivity can be wrong and biased.

Using the one-way ANOVA, it is possible to conclude that physical activity can affect productivity positively or negatively; high physical activity and high productivity are interconnected; the sedentary lifestyle leads to decreasing productivity. However, it is rather difficult to conclude what factors make people following the definite lifestyle to increase or decrease their productivity in relation to the hours spent to perform different tasks. The practical significance of the results is in the opportunity to apply the findings to the practices used by human resource management in order to improve the employees’ health and increase their productivity and performance.

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The question about the effect of physical activity on productivity should be researched because of its practical significance. Using a one-way ANOVA, it is possible to receive accurate results on the presence of differences in means and make appropriate conclusions. This statistical test can be effectively applied to the research question because it provides opportunities to determine actual differences between means with the help of posthoc tests.


American Psychological Association. (2010). Publication manual of the American Psychological Association. Washington, DC: American Psychological Association.

Huck, S. W. (2012). Reading statistics and research (6th ed.). Boston, MA: Pearson.

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