Descriptive statistic is a statistic analysis to describe the characteristic of the respondents (Pallant, 2013). This study employs descriptive statistical analysis which gives value of mean, median and standard deviation of the respondents based on several indicators, such as sex/gender, educational level, position at work and income of the respondents. By using these indicators, the researcher describes the profile of the respondents. Hence, it can give some valuable information about the respondents. Furthermore, the descriptive statistic is not enough to answer the research questions and it should be followed by other analysis tools such as exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation modelling
Both of these methods have advantages and disadvantages (Becker et al., 2012; Hair, Ringle, & Sarstedt, 2012). Accordingly, this study uses CB-SEM as the analysis tool. The IBM AMOS 22 is the programme’s software to analyse the model. There are some advantages of using CB_SEM, such as it can confirm or reject a theory and or to analyse the model fit (Hair et al., 2013). In addition, The CB_SEM has some assumptions that should be met, including multivariate normality, remove outlier, missing data and sample adequacy (Hair et al., 2010). According to Kline (2011), the number of samples for SEM should be 200 cases or more. Hence, this study tests all the assumptions before run the analysis. In addition, according to Hair et al. (2010), in conducting the CB-SEM, this study follows some stages, including develop a theoretical based model, construct a path diagram, convert the path diagram, choose the input matrix type, assess the identification of the model and modify the model into the final one. Moreover, in assessing the identification of the model, this study has to concern about the goodness of fit of the model. Thus, the goodness of fit criteria will discuss below (Hair et al.,
Hence, when it finished, this study creates the structural model. Fifth, developing structural model is a stage which converts the measurement model into the structural model. There are two ways to draw the structural model, including draw full model with all measurement items and parcel items or composite items (Byrne, 2010). This study uses the parcel’s items method to create the structural model. Last but not least, the structural model validity assessment uses the same criteria with the measurement model validity assessment. Further, this assessment will continue with the hypotheses testing and see the regression weight of the construct’s relationships. However, when the structural model is not fit, there are some ways to improve the model such as using the modification indices and standardised residuals of variance which should be less than 2.58 (Byrne,
Validity is extremely weak in this test. It appears that the main issues of this test deals with the weaknesses found in construct, predictive, and content validity. The test had two reviewers, and both agreed that this test was extremely flawed. The first reviewer stated that the CLT’s results were compared to the unknown top four standardized tests of achievement of the time. However, it should be questioned why were these specific tests chosen and what does the results reveal. The CLT did not answer those questions. The tests may or may not have been similar, but because we do not know what the unknown tests measured, the construct validity could be viewed as weak in this regard. The correlations (between .40 and .70) also showed that the data of the CLT yielded similar or different results of the tests that were compared. Or it could measure both result...
Construct Validity: Construct validity refer to how well a measure actually measures the construct it is intended to measure. It is related to the measure capturing the major dimension of the concept under study (Polit& Beck, 2010). The more abstract the concept, the more difficult it is to establish construct validity. Known group validation typically involves demonstrating that some scale can differentiate members of one group from another. The procedures in known group technique consist of an instrument being administered to be high and low on the measured concept.
In statistics, a population is a collection of individuals, things, events, etc. The population is the topic that one wants to make inferences on, whereas a sample is a subset of the population that is being collected—to be studied. After the sample is studied in statistics, one draws an inference of the population. There are four general sampling methods used in statistics: representative sample, random sample and quasi-random sample, stratified and quota sample, convenience sample, and purposive sample. A representative sample should be unbiased and thus properly indicate a characteristic of the entire population. In a random sample nothing is biased; in other words, every individual, thing or event in the population has the same chance of being selected for the sample. Therefore, because of the randomness of the sampling, the selection of one item from the population in no way effects the selection of another item. A quasi-random sample is simply a number (nth), which is
It took me all night but I did the assign work of writing. This writing assignment required me to pick two out of three question. i pick first and third question because i understand the question and completed them. The first question is about matching what statistic method on the three question implying the answer and what is the pros and cons of those statistical methods. The third question is proportional and finding the probability on it three question. The first part of this assignment is by do the conventional methods to find the question and knowing assign a label or attribute.
...determined a sample size of 1035 respondents in order to avoid non-normality of the data (Hair Jr., Anderson, Tatham, & Black, 2007). A quota sampling was utilized based on major cities in Pakistan on proportionate population basis. The cities are Karachi (n=523), Lahore (n=284), Faisalabad (n=114), and Rawalpindi/Islamabad (n=114). Data was collected through mall intercept. A typical multiple stage procedure for SEM was employed (Hair Jr, Black, Babin, Anderson, & Tatham, 2010) which is in inclusive of Exploratory Factor Analysis (EFA), ascertaining the reliability of the constructs (Leech, Barrett, & Morgan, 2005), measuring Convergent and Discriminant Validities, CFA for all the constructs, exogenous and overall model (Hair Jr, et al., 2010; Steenkamp & Van Trijp, 1991). Table 1 details the constructs used, item number, scale used, type, reliability and validity.
Three major types of methods used for this study are “Longitudinal Research Method”, “Cross- sectional Research Method” and “Cross Sequential Method” (A cohort form of Longitudinal and cross-sectional method). “Case Study Method” and “Survey Method” also have been used (Baltes, 1968).
Also, the title of the article states the research is a “population study” which is a focus of a quantitative research and a component of a quantitative method. Furthermore, the authors specified a clear defined research purpose which often requires statistical methods to test the hypotheses as well as to look for the cause and effects of the variables so that predictions can be
The empirical data offered by the Technical Manual shows strong and distinctive correlational findings, and consistent measures of the constructs the scales target. These findings provide strong evidence supporting the construct validity and reliability of the 51 Scales found in the MMPI-2-RF. There is much research supporting or opposing the claim of reliability in the MMPI-2-RF.... ... middle of paper ... ... Diagnostic construct validity of MMPI-2 restructured form (MMPI-2-RF) scale scores.
The authors of this article have outlined the purpose, aims, and objectives of the study. It also provides the methods used which is quantitative approach to collect the data, the results, conclusion of the study. It is important that the author should present the essential components of the study in the abstract because the abstract may be the only section that is read by readers to decide if the study is useful or not or to continue reading (Coughlan, Cronin, and Ryan, 2007; Ingham-Broomfield, 2008 p.104; Stockhausen and Conrick, 2002; Nieswiadomy, 2008 p.380).
Descriptive statistics refers to the collection, presentation, description, analysis and interpretation of a collection of data, essentially is to summarize these with one or two pieces of information (descriptive measures) that characterize all of them. The descriptive statistics is the method of obtaining a data set conclusions about themselves and do not exceed the knowledge provided by them. It can also be used to summarize or describe any outfit whether it is a population or a sample, as in the preliminary stage of statistical inference the elements of a sample known.
In this research study descriptive and empirical research approach have been follow because of the following
Likewise, in order to validate construct validity, Malhotra et al. (2012) recommends that in conducting research, researchers should use multi versus single-item scales to validate data from experiments, depending upon the complexity of the experiment. Malhotra et al. (2012) also recommends using a step-by-step approach ...
Now within the rest of this paper you will be finding a few different things getting discussed. Staring it off we will be discussing the articles that we have found to make our arguments and hypotheses. After wrapping up the literature reviews we will be discussing the hypotheses thus continuing onto our variables and indicators. Once we discuss our hypotheses we will be moving onto the research design. The research design will have our general issues, sampling, and methods.
The intention of this paper is to define the quantitative research and to explain the reasons why I choose this as a research approach. Regarding to Marczyk, DeMatteo & Festinger (2005) suggest, it is necessary to think carefully about an appropriate research design when the researcher wishes to answer specific questions, clearly define the variables and measure the hypothesis. Choosing the suitable research design is important because each type of research design has its own characteristics and methodology. Given this, is must be realized that all research designs have both strengths and weaknesses. Hence, the researcher must make an informed and personal decision about the match between the kinds of variables to be studied and the strength and weaknesses of the various methods (Herzog, 1996).
The research was designed using qualitative model based on exploratory design. This was done to facilitate multi-faceted study with a broader prospective. Basic percentage analysis was done to supplement qualitative analysis. The study was conducted with the help of a Questionnaire. To deepen the understanding data was collected from a variety of books, Internet web pages, and articles of different kinds conducted was descriptive in nature. Descriptive research includes survey and facilitating enquiries of different