Presentation on theme: "Advanced Research Techniques. Hello everyone……"— Presentation transcript:

Hello everyone……

Research? What does it mean?

The term of research can be defined as the scientific search for knowledge or, the systematic application of the scientific method to the study of problems. In other words, it is a systematic investigation to solve new or existing problems, prove new ideas or develop new theories.

There are three research types. These are; 1.Scientific Research 2.Artistic Research 3.Historical Research

Research Methods

Qualitative Research can be defined as the collection, analysis and interpretation of comprehensive narrative and visual data in order to gain insights into a particular phenomenon of interest. Qualitative researchers aim to gather an in- depth understanding of human behavior. The qualitative method investigates the why and how of decision making, not just what, where, when. Hence, smaller but focused samples are more often needed than large samples

Quantitative Resarch In the social sciences, quantitative research refers to the systematic empirical investigation of social phenomena via statistical, mathematical or computational techniques. The objective of quantitative research is to develop and employ mathematical models, theories and/or hypotheses pertaining to phenomena.

Quantitative researcher asks a specific, narrow question and collects numerical data from participants to answer the question. The researcher analyzes the data with the help of statistics.

Differences between Quantitative and Qualitative

Research Methods Quantitative *asks how much/how many? *tries to investigate objective realities, * is generalizable, *is deductive, *works with statistical/numerical data Qualitative *asks what/how?/ why? *tries to investigate subjective realities *is not generalizable *is inductive *works with words and meanings

Statistics What does it mean?

Statistics are techniques and procedures for analyzing, interpreting, displaying and making decisions based on data. In other words statistics is a way to get information from data. Statistics rely upon the calculation of numbers. For instance ; the largest earthquake was measured 9,2 on vector scale.

What is Data? How we can collect it?

Data means facts or pieces of information. We collect primary data by; observations, experiment and survey

For instance Ages of students in your classroom; 23, 26, 28, 30, 23, 25 IQ of five randomly selected individuals; 109, 89, 129, 101, 104

Types of data collection; What is primary data? We can collect data directly. This type of data is called primary data What is secondary data? We can use data which is collected by others (e.g Statistics Canada Market Research Company) this type of data is called secondary data.

What is Sample (subset) and Population?

Lets say you want to find the average GPA of a student at your university. Your university has 20.000 students and you select 100 students and ask them their GPAs. Your population is the group you are interested in studying (the 20.000 students) and your sample (100 students )is a small group ( a subset) you have taken from the population We can demonstrate this information with that picture which is below.

Descriptive Statistics Inferential Statistics

Descriptive Statistics

Descriptive Statistics can be described as data analysis techniques that enable a researcher to describe data with numerical indices or in graphic form In descriptive statistics we can use a graph, a chart or a table to show what you are describing. Descriptive statistics asks questions to describe data that we definitely know. What we watch on TV, types of automobiles that will be produced are influenced by Descriptive Statistics.

Inferential Statistics

According to Franken and Wallen (1990) Inferential statistics refer to certain types of procedures that allow researchers to make inferences about a population based on findings from a representative sample (p.173) According to Mills and Airasian (2006), Inferential statistics allow researchers to generalize to a population of individuals based on information obtained from a limited number of research participants. (p.337)

Thus we can say that we use a random sample to learn something about a larger population in inferential statistics. According to Mills and Airasian (2006), Inferences concerning populations provide only probability statements, the researcher never certain when making an inference about a population (p.379)

Differences between inferential and descriptive statistics

We use inferential statistics to make inferences from our data to more general conditions. We use descriptive statistics simply to describe what is going on in our data. So, we take a sample or a small subset of a larger set of date and then use this sample to draw inferences about the population as a whole with inferential statistics but we just ask questions to just describe data with descriptive statistics.

We are doing more than just describing with inferential statistics. We can compare groups, test a hypothesis and make predictions. We can also ask additional questions about the data. Lets watch another short video to get what I meant by asking additional questions about the data.

Testing (Statistical Hypothesis, data, groups…etc)

Researcher can study and investigate by testing a null hypothesis, using tests of significance ( two-tailed & one-tailed tests and t test) find standard error

Showing, Testing and Comparing Data in Inferential Statistics

In inferential statistics, a researcher can evaluate the data that he found and show his inferences with charts, graphs and interval scales. Two-tailed test One-tailed test Pie-chart Graph

What does HYPOTHESIS mean?

According to Mills & Airasian, Hypothesis is an explanation for the occurrence of certain behaviours phenomena or events, a prediction of research findings.

What does test of significance mean?

Test of significance is described as A statistical test used to determine whether or not there is a significant difference between or among two or more means at a selected probability level by Mills & Airasian

To be able to show what a researcher has found, test how true or false what have found and to be able to present his/her conclusions and inferences we should find out standard error and test the data with one-tailed and two-tailed tests, t-test and ANOVA.

One-tailed and two-tailed Tests

One-tailed Test: Fraenkel and Wallen described one-tailed test of significance as the use of only one tail of the sampling distribution when a directional hypothesis is stated and this type of test assumes that a difference can occur in only one direction. To select a one-tailed test the researcher has to be sure that a difference can occur in only one direction.

Two-tailed Test: Mills and Airasian describes it as Test of significance are usually two-tailed. A two- tailed test allows for the possibility that a difference may occur in either direction.

T-test:

According to Fraenkel and Wallen, t test is a parametric test of significance used to determine whether there is a significant difference between the means of two independent samples.

What does ANOVA mean?

According to Fraenkel & Wallen Analysis of variance is a technique for determining the significance of differences among means. It can be used with two or more groups. According to Mills & Airasian, Simple, or one- way, analysis of variance (ANOVA) is used to determine whether a significant difference exist between two or more means at a selected probability level.

References Fraenkel, J. R. & Wallen, N. R. (1990) How to Design and Evaluate Research in Education. McGraw-Hill Publishing Company. Mills, G. E. & Airasian, P. & Gay L.R. (2006). Educational Research (Competencies for Analysis and Applications. Pearson, Merrill Prentice Hall. Mouly, G. J. (1963). The Science of Educational Research (second edition). Van Nostrand Reinhold Company, Litton Educational Publishing.