Satisfactory Essays

- 1139 Words
- 3 Pages

Analytical Method

To analyze the influence of Work motivation factor towards job satisfaction and to know which job satisfaction factors that have the highest influence on job satisfaction, writer is using the multiple regression to analyze the influence of each work motivation factors towards job satisfaction. Furthermore, writer will use reliability and validity test and four classic assumption tests to measure the data.

Justification of the Data

Validity and Reliability Test

To justify the data from the questionnaire, writer will use validity and reliability test. The purpose of validity test it know whether the measurement items used able to measure the variable (Ghozali, 2001).

Ghozali (2001) stated a variable is reliable if the responds from the respondents are consistent across the research. The purpose of the reliability test is to measure the consistency of the measurement items. Writer are going to measure the variable‘s cronbach alpha to measure the internal consistency of variables. Ghozali (2001) added that if the cronbach alpha value of a variable is higher than 0.6 it means that the variable is reliable.

Statistical Method

Classic Assumption Test

When a research uses multiple regressions as the statistical tool, that research directly use several assumption (Lind and Marchal and Whaten, 2008). Thus, writer will use classic assumption tests to prove that these assumptions are correct.

Normality Test

Writer will conduct normality test in this research. The purpose of this normality test is to measure the distribution of the residual. Distribution of the residual in multiple regressions should follow normal distribution (Lind and Marchal and Whaten, 2008). There are two ways to conduct the normality test and...

... middle of paper ...

...f-test is the overall evaluator for the whole model and t-test is the evaluator for each of the independent variable. Thus, in this

T-Test

According to Cooper and Schindler (2011), t-test is a test to know the statistical significance of an independent variable towards dependent variable. Writers will compare the results of the t-test with the ANOVA table. Writer will compare the results of the T-test with the significance level of the research. If the significance level of the t-test is higher than 0.05 it means that the independent variable is not significant.

Adjusted R2

Adjusted r2 is a test to know the ability of the independent variable to predict the variance of dependent variable. Adjusted r2 ‘s value range from 0-1. The higher the value of the adjusted r2 means higher ability of the independent variables to predict the variance of dependent variables.

To analyze the influence of Work motivation factor towards job satisfaction and to know which job satisfaction factors that have the highest influence on job satisfaction, writer is using the multiple regression to analyze the influence of each work motivation factors towards job satisfaction. Furthermore, writer will use reliability and validity test and four classic assumption tests to measure the data.

Justification of the Data

Validity and Reliability Test

To justify the data from the questionnaire, writer will use validity and reliability test. The purpose of validity test it know whether the measurement items used able to measure the variable (Ghozali, 2001).

Ghozali (2001) stated a variable is reliable if the responds from the respondents are consistent across the research. The purpose of the reliability test is to measure the consistency of the measurement items. Writer are going to measure the variable‘s cronbach alpha to measure the internal consistency of variables. Ghozali (2001) added that if the cronbach alpha value of a variable is higher than 0.6 it means that the variable is reliable.

Statistical Method

Classic Assumption Test

When a research uses multiple regressions as the statistical tool, that research directly use several assumption (Lind and Marchal and Whaten, 2008). Thus, writer will use classic assumption tests to prove that these assumptions are correct.

Normality Test

Writer will conduct normality test in this research. The purpose of this normality test is to measure the distribution of the residual. Distribution of the residual in multiple regressions should follow normal distribution (Lind and Marchal and Whaten, 2008). There are two ways to conduct the normality test and...

... middle of paper ...

...f-test is the overall evaluator for the whole model and t-test is the evaluator for each of the independent variable. Thus, in this

T-Test

According to Cooper and Schindler (2011), t-test is a test to know the statistical significance of an independent variable towards dependent variable. Writers will compare the results of the t-test with the ANOVA table. Writer will compare the results of the T-test with the significance level of the research. If the significance level of the t-test is higher than 0.05 it means that the independent variable is not significant.

Adjusted R2

Adjusted r2 is a test to know the ability of the independent variable to predict the variance of dependent variable. Adjusted r2 ‘s value range from 0-1. The higher the value of the adjusted r2 means higher ability of the independent variables to predict the variance of dependent variables.

Related

- Good Essays
## The Chi Square Test For Independence

- 810 Words
- 2 Pages

The Chi-Square is used in two circumstances as below: i) When the researcher want to estimate how closely the observed distribution matches the proportions that is expected. This is called ‘goodness of fit’ test. ii) When the researcher wishes to estimate whether random variables used are independent. Assumptions of the Chi-Square Test: i) To use Chi-Square test for independence, the two variables that are used must be of categorical data i.e. the data ought to be measured at nominal or ordinal levels.

- 810 Words
- 2 Pages

Good Essays - Good Essays
## Correlation And Regression Analysis

- 911 Words
- 2 Pages

Regression is a hypothetical model of the relationship between the two variables. The similarities between them are, they both are statistical analyses used to identify the relationship between the predictor and the outcome variable. What is a line of best fit, what does it tell us, and how is it developed? The line of best fit is a linear line that minimizes error within a data set. It helps to

- 911 Words
- 2 Pages

Good Essays - Good Essays
## Descriptive Statistics: Raw Data

- 756 Words
- 2 Pages

Data collected were analyzed by using three approaches: 1. Cronbach’s alpha (a) was used to test the reliability. Cronbach’s alpha indicates how well the items in a set are positively correlated to one another. This is to make sure that the scales are free of random or unstable errors and produce consistent results over time (Cooper & Schindler, 1998); 2. Descriptive statistics where the researcher used mean, standard deviation and variance to get an idea on how the respondents reacted to the items in the questionnaire.

- 756 Words
- 2 Pages

Good Essays - Satisfactory Essays
## Descriptive Research Methodology

- 2842 Words
- 6 Pages

The self-administered questionnaire is a technique used to engage in the needed data collection. Zikmund (2004) stat... ... middle of paper ... .... Multiple regression is a technique that allows additional factors to enter the analysis separately so that the effect of each can be estimated. Malhorta (2004) explained that multiple regression analysis is a way to describe the relationship between a dependent variable and several independent variables. In the multiple regression, one uses additional independent variables that help better explain or predict the dependent variable (Y).

- 2842 Words
- 6 Pages

Satisfactory Essays - Satisfactory Essays
## Essay On Structural Equation Modelling

- 920 Words
- 2 Pages

(Holmes-Smith, Coote, & Cunningham, 2004) On specification the model is then tested for plausibility based on the sample data that comprise all observed variables in the model. The main task in model testing is to determine the goodness-of-fit between the hypothesized model and the sample data. Fit Indices There is abundance of fit indices and wide variety of disparity in agreement on which indices to report and also the cut-offs for various indices, (Hooper, Coughlan, & Mullen, 2008) because dif... ... middle of paper ... ...are the options to verify the dimensionality of the measurement or to verify the model fit. The modification of the model is aided by modification indices (MIs) sometimes in conjunction with parameter estimates statistics. (Lei & Wu, 2007) These indices were examined during evaluation of model fit to get the direction of modification, for example whether freeing or incorporating parameters either between or among unobserved variables is required in obtaining better model fit.

- 920 Words
- 2 Pages

Satisfactory Essays - Best Essays
## Validity: External, Internal, and Construct

- 2019 Words
- 5 Pages
- 5 Works Cited

However, quantitative practitioners affirm the cause or effect interplay between data and construct for validation of investigation by applying test procedures or processes (Golafshani, 2003, p. 599). As a result, with regard to validity, researchers conclude that, it is whether measurements of the mean are accurate or they are measuring the intended features. Accuracy of the mean helps in relating the cause-and-effect relationship present in internal validity. The above definition is associated with quantitative research methodology. It summarizes that validity to be the extent in which instruments measure the exact thing it purports to measure.

- 2019 Words
- 5 Pages
- 5 Works Cited

Best Essays - Powerful Essays
## Experimental Methods Used in Applied Research

- 1688 Words
- 4 Pages
- 3 Works Cited

Moreover; I will examine true experiments and examine how they control threats to internal validity. In addition, I will examine how true experiments are different from experimental designs. Finally, in this paper, I will discuss quasi-experiments by explaining their importance and how they differ from experimental designs. According to Shaughnessy, Zechmeister, and Zechmeister (2009), data analysis and statistics play a major role in the analysis and the interpretation of experimental findings. Descriptive statistics and inferential statistics are both used to describe the results of an experiment.

- 1688 Words
- 4 Pages
- 3 Works Cited

Powerful Essays - Satisfactory Essays
## Review of paper 1

- 1491 Words
- 3 Pages

1. Introduction Design variables are important to be conducted the appropriate experiment analyzing and getting the accurate values for integer, discrete, zero-one (binary), and continuous variables. The researchers should classify design factors before the experiment is conducted. In literature, there are several factors such as quantitative, qualitative, discrete, continuous, zero-one (binary), non-zero-one (non-binary), controlled and uncontrolled variables (Sanchez & Wan, 2009). Quantitative variables get numerical values.

- 1491 Words
- 3 Pages

Satisfactory Essays - Good Essays
## Measurement Scales

- 837 Words
- 2 Pages
- 2 Works Cited

In order to predict and gauge the consumers responses to a questionnaire correctly the questionnaire must be assembled with the appropriate guidelines to attain the desired statistical results. Works Cited Lane, D. (2003). Levels of Measurement. Retrieved from http://cnx.org/content/m10809/latest/ Stat Trek. (2011).

- 837 Words
- 2 Pages
- 2 Works Cited

Good Essays - Good Essays
## Examples Of Quantitative Methodology

- 1033 Words
- 3 Pages

It has objective stances, logic, and numbers focusing on unchanging data and details (Babbie, E.R., 2010). For example, a quantitative method would ask how many people are participating in a program, what are the characteristics of people in a program, and how do the people in the program perform (Leedy, P. & Ormrod, J., 2009). Using a quantitative research method has several advantages for testing the hypothesis. The aim of quantitative research is to classify features, count the features, and construct statistical models to explain what was observed (McNabb, D.E., 2008). Typically, quantitative methodologies uses already tested and validated theories about how and why an event occurs.

- 1033 Words
- 3 Pages

Good Essays