Application Assignment Part 1: Charting Your Growing Knowledge Week 5: Understanding Research Angie Woods

Application Assignment  Part1: Charting Your Growing Knowledge Week 5: Understanding Research   1

Application Assignment Part 1: Charting Your Growing Knowledge  Week 5: UNDERSTANDING RESEARCH

Student Name: Angie Woods EDUC- 6163 - 3 Building Research  Instructor: Jan Ferrari Walden University

Application Assignment Part 1 Part 1: Charting Your Growing Knowledge Week 5: UNDERSTANDING RESEARCH

Chapter 8 Quantitative designs and statistical analysis

Student Name: Angie Woods

SECTION 1: KEY TERMS

WEEK 5 Online reading: “Introduction to Variables” and “Quantitative Designs: An Overview”	TERMS USED	DEFINITION OF TERMS
	1.      Parametric	It is a statistics used when variables are measured as a quantity is parameter. The measures must be based on an interval scales. Which the parametric tests are assumed to the sample score of a normally distributed is symmetrical about the meaning.
	2.Non-parametric statistics	It is only used when assumption are normal distribution that cannot be met.  This only happen in most cases that can occurs only when a variable does not quantify that is based on nominal or ordinal groupings.
	3.Internal reliability	This is the degree to which the indicators or even items that may make up a scale for example from a questionnaire that are consistent will inter-correlated.

SECTION 2: LEARNING RESOURCE HIGHLIGHTS

TOPIC - WEEK 5	TOPIC SUMMARY	PERSONAL COMMENT
Quantitative Research learning resources highlights	The quantitative research is an aspect of much objectivity that introduces the controls into research designs. The research questions of a set of measurable variables that are reliability determines the accuracy of many measures. The key measurement that a features quantitative design is independent, dependent and control variables that are defined in a measurable of terms. Now the nature of the measures determines the types of statistical analyses which can be applied to the data.  Once doing analysis of the data the data proceeds systematically. In a descriptive statistics of a summaries in the distributions in many variable. The bivariate statistic in analysis of the data it identify relationships among the set of variables. But in the final stage of the quantitative research study the main thing is that the researcher do interprets the most value in applicability with limitations about findings. But one I almost forgot to discuss in analysis is inferential statistics test that is an extent to the result that can generalize to a wider population. For an example a big selection of data to choose from then can analysis it better. That’s just what I think it would be better for me. Still of have a limited of results to choose from the research may not be so good.	My personal comment about quantitative research is setting of the data up in the form of a research questions. I feel like the purpose and benefits I can gain out of this are a better and clear way of understanding some of the research questions. The quantitative research it showed me a method why I can prefer this approach in the type of research questions more of addressing a range of questions. To be benefited to me with understanding what my research is all about with the main points or ideals of the topic.

SECTION 3: REFLECTION

Week 5 The question I would have for my reflection would be in the text book on page 152. Compare the total number of subjects described in Tables 8.3 and 8.4. Why are there fewer children in Table 8.4?

In Table 8.3 as the author would say, it was analysis in an inferential statistics which the researcher seeks to test of hypotheses that establish causation in making generalized statements. The significance of the result for the wider population. By what the author say, Inferential statistics examine the relationships between the dependent variable and independent and control variables, by drawing on multivariate methods of analysis to simultaneously assess the contribution, and significance, of the variables. In Table 8.4 this Table analysis with the examined of the relationships that is between the dependent variable. Like the infant mother attachment security with the independent variable in the amount of child care received. As the author say, results showed that secure attachments were more likely when children attended part time 73.8 per cent secure or full time 67.7per cent secure hours of care, and less likely when children attended for minimal hours 36.8 per cent secure. Still as the author would say about Table 8.4 in a stage examined the relationship between the dependent variable, in an independent variable (age of starting child care) and relevant control variables (maternal age, education and depression, and child temperament). The author says, Note that the independent and control variables are metric and distributed across a range of scores. So in Table 8.4 the range of the population is smaller it’s not the same size as Table 8.3 amount of children. By Table 8.4 being much more of a smaller group. It determines the amount of care received for the coverage of having fewer amount of children that has the amount of informal child care. I just think according to fewer children and age group its limited of what all can be done. Informal care has no increase chance of security in regardless of the hours that’s’ attended with children part time care.