Research Method, Professional Training For Police Officers, And Impact Of Education On Trainee Motivation - Essay.

List at least 10 variables that would be collected in your mock research project that would be used to answer the hypotheses. After each variable, list the variable name you will use in SPSS (Section C), the level of measurement (binary, nominal, ordinal, interval, or ratio), and the possible range of scores. Feel free to be creative.

Research Method and Variables Selections

The purpose of this study is to understand the perspective of research. Why and how research is done and the to understand the importance of Research method. The definition and selection of variables and understanding how it effects the purpose and outcome of research. Also, to understand the use of descriptive statistics to study data and understand variations in data.

Need of professional training for Police officers in the United States. It is believed that professional police training and education will help to develop the minds, career plans and attitude of the future officers.

The aim of this research study is to assess whether level of education will impact trainees’ motivation during initial police training. 

The required variables are gender, age, education, place, training expectation, motivation 

Dependent Variable: Motivation to learn is the dependent variable selected for this study. It will be measured using a five-point Likert scale ranging from “strongly disagree” to “strongly agree”, based on statements of trainees’. We will assess trainee motivation to learn using questionnaire that were filled up by trainees’. The questionnaire aims to gather information related to trainee motivation during the training as well as prior expectation regarding police training.

It is difficult to decide variables with interval and ratio level of measurement as these are continuous variables and show the equal difference from number and in ratio with other numbers on the given measurement scale. In case of ratio variables, the scale needs meaningful zero point as this facilitates correct comparison between items represented on the scale like A having value 40 and B having value of 20, provides information about the difference of age between them. We can say A is twice as old as B or the difference in their age is 20. Here, age can be considered as interval and ratio variable, but it entirely depends on measurement. 

What effect does higher education have on trainee motivation to learn during initial training at the police academy. It is expected to find relationships between higher education and motivation to learn.

Null Hypothesis: H0  

Higher education degrees will positively affect trainee motivation to learn during police training

Alternate Hypothesis: H1

Higher education degrees will not positively affect trainee motivation to learn during police training 

This research idea is more Correlational research because of the following points:

• The defined variables training expectation & motivation are dependent variables and can vary with change in other independent variables. However, this research question can be scientifically proven with the help of survey questionnaires to be filled by trainees and interviews of the instructors and we cannot bring any change to any variable. We are just trying to observe the change.
• Data about response to questionnaires needs to be collected and the training curriculum needs to be analyzed. Here we cannot see the change in dependent variable (motivation in training) by changing independent variable (level of education). We are not trying to influence what happens when manipulating variables.

Experimental Research:

• Helps to see the change in dependent variable (motivation in training) by changing independent variables (level of education).

Correlational Research:

• Helps to relate two or more variables to understand any relation between them like checking the change in motivation in training at different level of education.
• We cannot manipulate the level of education (independent) to verify the motivation in training. (dependent) It will tell nothing about the causal influence of the level of education.

These are measures to check and reduce the measurement error. Reliability in this research questions whether does level of education measures the required level of education. The level of education is valid only if there are no other factors other than which we are interested in that can influence them.

Need for Professional Training for Police Officers

Validity talks about the ability of the measure to generate same results under the same conditions. To check validity, the instruments needs to be reliable. Validity of level of education can be proved by measuring the impact of level of education on the same set of trainees twice.

Validity is necessary nut it is not the sufficient condition of a measure and thus to reduce measurement error, we need to ensure the reliability and validity of the measure i.e., impact of level of education.

We cannot have one without the other or we can say the test of correct measurement is incomplete without each other. Validity depends on reliability and reliability alone does not suffice the results. Here measure refers to variables taken into consideration. To get accurate results, we need accurate measures. Reliability & validity together provide an accurate measure. 

In this research study, I want to check the impact of level of education on the motivation in Police training on trainees. To research on this problem statement in the US, practically it is not possible to get the questionnaire filled by each individual and to collect data of such large audience. This is not a feasible approach.

To get the substantial information from members of this group, there is another approach to collect the data and conduct interviews that represents the population without actually asking the entire population. We will need to get a sample.

Population: A population is all members of a specified group. Each individual trainee taking the Police training in the US.

Sample: A sample is a part of a population which describes the whole group. Pick random number of trainees who are taking or got enrolled for Police training in the US. The number can be 100 trainees but needs to be random and unbiased.

It is a crucial step to understand the difference between a sample and population in a statistics course:

• Helps in generating better data collection
• It is easier to infer the things from the sample about the population.
• The bigger the sample size, the more will it reflect the whole population.

The given sample of 20 observations of weight (in pounds) was used to check measures of central tendency: 

Mean: The average weight in pounds in this sample is 126.25. The disadvantage with mean value is that it can be influenced by extreme scores. Mean is also affected by skewed distributions and cab be used only with interval or ratio data.

Median: The middle weight in the sample of 20 observation is 115.

Mode: The weight which occurred the most in the sample is 115 pounds.

Impact of Education on Trainee Motivation

Median is relatively unaffected by the extreme scores at either end of the distribution and relatively unaffected by skewed distributions and can be used with ordinal, interval and ratio data.

Mean is effective measure of central tendency and best describes the data because it uses every score taken in the data set whereas median and mode ignores most of the scores in the data set. Mean value tends to be stable in different samples. 

This measure helps to understand the spread of data.

Range: It is the spread of data in the sample which is calculated by subtracting the lowest score from the highest score and this value comes to 175. The advantage with range calculation is that it is affected by extreme scores due to use of only highest and lowest score in the sample.

Interquartile Range: It is range of the middle of the data, calculated by excluding top and bottom 25% of the scores. This range is not affected by extreme scores at either end of the distribution.

Interquartile range (IQR) = upper quartile (Q3) – lower quartile (Q1)

                                             = 117.00 – 105.50

                                             = 11.50

Variance: Variance show the average dispersion in the data. It is the average error between the mean and the observations. This measure is calculated in square units and this becomes difficult to talk about this error in units of the given data.

Standard Deviation: To overcome the problem of variance, we take the square root of the variance to get the average error in the same units as the original measure. This value simply tells the deviation of data around the mean. If the value of standard deviation is smaller than mean that shows that data points are close to mean and a higher value than mean indicates that data points are far from the mean.

Here, the standard deviation is 47.165 and mean value is 126.25, so the deviation of data points is less from the mean.

These values help to understand that there is not much deviation from the mean. All data points are close to the mean values.

Statistical Significance

Null Hypothesis: H0  

Higher education degrees will positively affect trainee motivation to learn during police training

Alternate Hypothesis: H1

Higher education degrees will not positively affect trainee motivation to learn during police training 

In this research study, no statistical test is conducted on the Null Hypothesis. Th aim of this research study is to collect data through surveys and interviews and conduct data analysis to support the theory and prove the stated Null hypothesis.

However, we can compute a test statistic that will represent the alternate hypothesis and help in calculating the probability that will get a value equal to the one we get if the null hypothesis was true. If this probability is less than 0.05 (5%) we reject the idea that there is no relationship between level of education and the motivation in police training for trainees’ and vice-versa.

The significance of the test statistic is directly linked to the sample size: the same effect will have different p-values in different sized samples.

Type I & Type II Error

While doing this statistical test to support the hypothesis there is a probability of making two types of errors.

Type I Error: Type I error occurs when we reject a null hypothesis when it is true, and the significant level of test is the probability of making a Type I error. Once we decide on the significance level, there is nothing else we can do about alpha.

Type II Error: A type II error occurs when we accept a null hypothesis that is false; the probability of type II error is beta. We would like this beta to be as small as possible or we would like (1 – beta) to be as large as possible. Because rejecting a null hypothesis when it is false is exactly what a good test should do, a high value of (1 – beta) means that the test is working quite well (it is rejecting the null hypothesis when it is false). A low value of (1 – beta) means that the test is working very poorly (its not rejecting the null hypothesis when it is false). Because the value of (1 – beta) is the measure of how well the test is working, it is also known as the power of the test.

References

• Binu, V. S. (2014). Some basic aspects of statistical methods and sample size determinattion PMC, Pages 119 - 123.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4279315/

• DePersio, Greg.What are the advantages of using a random sample to study a larger population INVESTOPEDIA

https://www.investopedia.com/ask/answers/042915/what-are-advantages-using-simple-random-sample-study-larger-population.asp

• Field, Andy. (Year). Discovering Statistics Using IBM Statistics 4^th

Los Angeles: Sage Publications Ltd.

• Levin, Richard.I. (2016). Statistics for Management 7^th

India: Pearson Publications