Quantitative Methods Module

WEEK 10:     Using SPSS I (descriptive and inferential) Hello in the week 10 everyone,  This week we are getting to know the SPSS program. Nowadays , it’s undeniable that research plays enormous impacts on people’s life. The most important tool to support the success of research is that statistics used. There are several computer programs developed for helping researchers conducting research easier in terms of quantified data analysis. This week we will discuss about one of the common used program is SPSS.  SPSS stands for Statistical Package for the Social Sciences. The SPSS is a  statistical software. It was produced by SPSS Inc., and it was acquired by IBM in 2009. My experiences with SPSS I used to approach to the SPSS program in 2012 when I analysed data for my Master degree. Personally, I particular like this program because it was not too difficult to deal with.  The most important part is that we need to know what statistics ...

WEEK 9:   Item response theory  (Mokken scaling) Hi, everyone I feel that the assignment in this week is an important topic (and it is really difficult to understand) in the health science research.   We will discuss about the i tem response theory (Mokken scaling) in terms of how this being used in the social sciences. First of all, in the blog I will explain how  Item response theory differs from Classical test theory .  Classical test theory Classical test theory (CTT) is a traditional quantitative approach to test the reliability and validity of a scale based on its items, usually set up only one version of the test that covers all elements of the feature or content that you want to measure with various of the difficulty level of the test. There is no definite proportion of difficulty level. Moreover, we have to set up a large number of questions (To Find the quality of the test requires the difficulty level (p) and the discrimination (...

Week 8; Factor analysis In this week we will discuss about the factor analysis on its meaning, objectives, types of factor analysis, and pros and cons of using factor analysis.  Factor Analysis Factor analysis is a statistical technique to group or combine variables that are related both positive and negative in the same group. The central aim of factor analysis is the "orderly simplification" of several interrelated measures using mathematical procedures. Variables within the same factor is highly correlated while variable within the difference factor is less or no correlated. It can be used to develop a new theory or confirm the generalization. Why use factor analysis Factor analysis is a useful tool for all sciences that are concerned to discover if variables from regular patterns and vary together.  1. To investigate whether the common factor explained the relationship between variables, where the number of common factors is less than the numbe...

Week 7: Quantitative analysis 2 Hello all, today I am asked to reflect about the  Inferential statistics. as the previous posted the way I need to learn always starting with the definition and how to used, so let's explore it together!!  I 'm trying to understand and distinguish between descriptive and inferential statistics in my own way. If you have some discussion, please do not hesitate to discuss more closely about this topic.  The annual income of the Amy clothing company  (Million pound) Year Winter Spring Summer 2015 6.2 7.5 10.0 2016 6.3 7.6 10.2 2017 6.2 7.6 9.8 2018 6.4 7.7 11.0           According to the table,   descriptive statistics c an be used to tell us about the value of the number in the table. For example, the most sale is in the summer each year. But   inferential statistics is ab...

Week 6: Analysis 1 (Descriptive) Descriptive Statistics In this topic, it will be discussed about we are interest in and experiment that we can not measure it directly. In this case how do we know the true value and the precision for the result of the quantities for the measurement actually made.  Descriptive statistics  give information that describes the data in some manner. We can describe this type of statistics by using description or numbers (mean, median, mode) and using graph, figure. It is worthwhile to note that we can not use the descriptive statistics for all data . By this it means that we can use within the assumption when the data has a normal distribution   that  shows a characteristic of central tendency. Mean = Sum of the values/ total number of values  Median = A set of number is found by listing the number in ascending order and then selecting the value that lies half way along the list          Ex...

Week 5:   Quantitative design II (Survey) Hi my blog's friends t hank you for your visiting my blog. This is the week 5 of the assignment in the Professor Roger module. We can say that it is so far...so good, isn't it? Today we will discuss about survey study design. These section contains three elements including   the definition of survey study design, types, and strengths and limitations of each type. Let's go to explore them!! Survey study design   is used to describe the possibilities or the relationship of variables in large areas. The 2 main  types of the design  ☝ Cross-sectional study is a study  on  the current situation or event with huge target population where only  ONE  set of observations is collected for every unit in the study, at a certain point in time, disregarding the length of time of the study as a whole. ✌ Longitudinal study i s a study on a long-term continuous event where  ...