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Human Resource

Name

Institution

Date

Human Resource

Central Tendency

In the measure of central tendency, the use of mean, mode or median is common. Either measure depends on various characteristic of the data. The use of mean is the most common measure of central tendency. It is referred to us as average. Mean is used when measuring tendency for both continuous and discrete data. A person finds the sum of all variables in the data and divides it to the number of values provided in the data set. Using mean is important as it includes all variables in the data set. Mean is better when sample size is large and when it does not contain outliers.

The median measures the middle score for any data set arranged using an order of magnitude. Notably, median is less affected by skewed and outliers data. Instances when median is the best measure of central tendency include when there are few extreme scores in the data set distribution. Mean is affected by single outliers but median does not. Second, when there are undetermined or missing values in a data set, the median is better. Third, when dealing with open ended distribution and the data is on an ordinal scale, median gives best tendency measure than mean.

The mode gives the most common variable in the data set. Mode is commonly used when considering data in a nominal scale. Mode is rarely used as it does not depict the best measure of central tendency when a common variable is far away when compared to the rest of the data set.

Multiple Regression

Multiple regression is more of an extended linear regression. It measures the value or relationship between a dependent variable (criterion or target variables) using two or more independent variables (explanatory, regressor or predictor variables). In the human resource domain, high employee performance is vital in attaining increased overall return in an enterprise. Employee performance is determined by other factors like fair remuneration and incentives, training and development program, supervision, good working environment and job security among others. In determining the employees’ performance as the dependent variable (target), the independent variable will be fair remuneration and incentives, training and development program, supervision, good working environment and job security.

The assumption of the dependent and independent variables satisfying the use of multiple regression include the dependent variable having a continuous scale. The independent variables must be either categorical (nominal or ordinal) or continuous. The independent and dependent variables should have a linear relationship. The data should show homoscedasticity where the line of best fit remains similar. Moreover, the data must not have multicollinearity to eliminate confusion on which independent variable contributes variance in dependent variable. Moreover, no significant outliers, high influential points or high leverage points should occur when performing multiple regression analysis. Lastly, errors must be normally distributed to present the best result in the regression.

ANOVA

The analysis of variance (ANOVA) determines statistical significant difference between means of independent groups. There is two type of ANOVA namely, one-way ANOVA and two-way ANOVA where there are one independent variable and two independent variable in the test respectively. Taking an example in a human resource field, the HR department wishes to determine the level of occupational stress based on age. The group gets classified into ages 35and below, 35-49 years and 50 years and above; groups are randomly split.

Using one-way ANOVA test in the example given above, a person determines the mean score of occupational stress for each group. A person set the confidence level in this instance at 95%. The p-value plays a major role of determining the statistical significance. When the mean is less than or equal to the p-value, a person rejects the null hypothesis and conclude that the population mean are equal. On the other hand, if the p-value is greater than the significance level set, a person accepts the null hypothesis that not all population means are equal.

The basic condition while using ANOVA analysis are; the dependent variable are normally distributed, homogeneity of variance as well as independence of all observations made.

Risks

During a research, human participant may be exposed to physical, economic, social, and psychological or health risk that affects their after-life. Therefore, researchers must develop some techniques to mitigate the risk associated with the study. First, researchers should provide the consent form to the participants. Participants in a research study make the decisions that fit them when offered an accurate consent process. If the participant accepts, it means the risks are manageable; there are exemptions to the vulnerable and risk sensitive participants. There should be excellent data collection and storage measures to avoid loss of confidentiality which is a possible risk in research study. Lastly, when the undesirable event happens, researcher should have a contingency plan to alleviate the victims from such risk. It includes having the right medical practitioner always ready to treat the incidences or accidents experienced.

However, sometimes the benefits of the research outweigh the potential risks to human participants. Whenever the results of the research develop a cure for the society mostly in medical studies, the research study outweighs the risk. Similarly, in the event that the research result guides the development of policies used as reference to community wellbeing, and the harm is at minimum as determined by the researcher, the research should continue.

Application of Research Methods

Various aspects of research methods are applicable in life. Ethics is a significant concept which assures that the researchers gets the prerequisite authorization to conduct research. The various ethic bodies ensure that human participants are not exposed to harm, their confidentiality is maintained, and the study is in line with moral standards of the society and specific discipline. Seeking the sample population is also important in life. Notably, a sample population should represent the general population for the results to provide a comprehensive knowledge/information about the population. Therefore, there should be prudent choice of an appropriate sampling design and data collection methods based on the population under study

Given the two types of research studies qualitative and quantitative determining which method to use gives a favorable method to evaluate situation in the world. Qualitative method undertakes the use of primary and measurable data while quantitative evaluates secondary and non-measurable information. Lastly, the statistical analysis of data is significant to determine a conclusion of the research study. It is through statistical or data analysis that research get inference to make conclusion and propose future research studies.

Two issues I would like to study using research methods include:

Which factors determines job satisfaction in employees?

How human resource hiring determines a company’s future profitability index