Expe-bma-pmet

3 Types/Categories of Statistics:
1)
Descriptive ? used when the purpose is to summarize and characterize a set of data
e.g. frequency, percentage, mean
2)
Correlational ? used when the purpose is to predict future behavior (because
relationship between or among variables is established)
e.g. Pearson correlation coefficient
Spearman rank-order correlation coefficient
3)
Inferential ? used when the purpose is to use a small sample of data from a
population to understand the entire population.
e.g. Chi-square, Analysis of variance

Where and Why Correlations are Used
•
Prediction – if two variables are related in some systematic way, it is possible to use one variable to make accurate prediction about the other. Example: the scores of Math in the USTET could be used to predict the performance of first year students in Math.
•
Validity – suppose that a psychologist develops a new test to measure intelligence. How could you be sure that the test really measures intelligence? This can be determined by checking the validity of the test. One common way is to check if the new test is correlated with an established intelligence test or other factors related to intelligence.
•
Reliability – correlation can also be used to determine a test’s reliability. A new test is considered reliable to the extent that it produces stable and consistent measurements. For a example, if your IQ were measured as 113 last week, you would expect to obtain nearly the same score if your IQ were measured again this week. When reliability is high, the correlation between two measurements should be strong and positive.
•
Theory Verification – many psychological theories make specific predictions about the relationship between two variables. For example, a theory may predict a relationship between brain size and learning ability. The prediction of the theory could be tested by determining the correlation between the two variables.

Parameters – values/characteristics that refer to or were obtained from a population.

Statistics – values/characteristics that refer to or were obtained from a sample

(1)
Median >> divides the distribution into 2 equal parts.
(2)
Quartile >> divides the distribution into 4 equal parts: Q1 (first quartile), Q2 (second quartile – equivalent to median), Q3 (third quartile), and Q4 (fourth quartile).
(3)
Decile >> divides the distribution into 10 equal parts: from D1 (first decile) to D10 (tenth decile).
(4)
Percentile or Centile >> divides the distribution into 100 equal parts: from C1 (first centile ) to C100 (one hundredth centile)

RANGE – (a) exclusive range - defined as the difference between the highest and the lowest score/value in an ungrouped data set; (b) inclusive range - defined as the difference between the exact upper limit (upper class boundary) of the highest score and exact lower limit (lower class boundary) of the lowest score in a grouped data.