Some terminology for statistics in educational research
1. Qualitative versus quantitative research
Qualitative Research - data typically in narrative form; gathered by use of observations and interviews; results contextual - unique to individual and setting.
2. Quantitative research - data numerical; gathered by quantifying observations, administering tests and other instruments; results generalizable - attempts to find laws, generalizations. Measurement
3. Measurement - assigning numbers to observations according to rules. Variables
Variable - a measured characteristic that can assume various values or levels.
* Discrete variables - have only certain values (whole numbers for example).
* Continuous variables - can take any value (accuracy of measurement).
4. Constants
Constant - has only a single value. A certain characteristic (like grade level) can be a variable in one study and a constant in another study.
5.Scales of measurement
* Nominal scale - naming, used to label, classify, or categorize data (gender, SSN, number on athletic jersey, locker number, address).
* Ordinal scale - classification function plus observations are ordered, distance between adjacent values not necessarily the same (olympic medals, finishing place in a race, class rank).
* Interval scale - classification, ordered plus equal intervals between adjacent units (all test scores are assumed to be at the interval scale, temperature Fahrenheit, temperature Centigrade).
* Ratio scale - all of the above plus the scale has an absolute zero, a meaningful zero. Most physical measures are at the ratio level of measurement (height, weight, distance, time, pressure, temperature on the Kelvin scale - absolute zero is -273 degrees Centigrade).
6. Descriptive and inferential statistics
* Descriptive statistics are a way of summarizing data - letting one number stand for a group of numbers, can also use tables and graphs to summarize data.
* Inferential statistics - research statistics, a measure of the confidence we can have in our descriptive statistics, the statistics we use to test hypothesis.
7. Parametric and nonparametric statistics
* Parametric statistics - used with interval and ratio data and usually with data that were obtained from groups randomly assigned, normally distributed, and with equal variability between groups - preferred statistics to use, they are more "powerful" than nonparametic statistics. Examples we will study are t-tests, analysis of variance, and Pearson correlation coefficient.
* Nonparametric statistics - used with nominal and ordinal data and sometimes with interval and ratio data when other assumptions can not be met. Examples we will study are the chi-square test and the Spearman rank difference correlation coefficient.
http://www.mnstate.edu/wasson/ed602lesson1.htm
--------------------
And also go through this link
http://www.stats.gla.ac.uk/steps/glossary/index.html
2006-07-04 02:04:41
·
answer #1
·
answered by Guru 3
·
0⤊
0⤋