PURPOSE "END SOUGHT" TYPE OF RESEARCH TYPE OF INDEPENDENT VARIABLE DESCRIBE STATUS --How cases distributed on variables --EXPLORATORY relationships between variables Descriptive - Survey Characteristics --used to describe only --not classified as independent or dependent

PURPOSE "END SOUGHT" TYPE OF RESEARCH TYPE OF INDEPENDENT VARIABLE --EXPLANATORY relationships between variables that are expected to exist on the basis of some rationale Variables that can be manipulated but are not manipulated EXPLAIN - PREDICT OUTCOMES Descriptive - Correlational Descriptive - Ex Post Facto Characteristics Has independent and dependent variables

PURPOSE "END SOUGHT" TYPE OF RESEARCH TYPE OF INDEPENDENT VARIABLE CONTROL OUTCOMES --CAUSE - EFFECT relationships between variables Has independent and dependent variables Active Variable- - major focus Experimental

SPECIFYING STUDY'S PURPOSE Type of Study Surveys, Case Studies, or Correlation Ex Post Facto or Experimental Appropriate to Use Research Questions or Objectives (Exception: Hypotheses about significant differences between groups, e.g., comparative surveys) Hypotheses

CHARACTERISTICS OF PROPERLY STATED OBJECTIVES 1. Stated as specific questions or objectives to be answered and/or research hypotheses to be tested.

CHARACTERISTICS OF PROPERLY STATED OBJECTIVES (continued) 2.Variables being investigated are specifically identified. A. Variables (characteristics) are given operational names -"achievement of student" becomes score on the XYZ achievement test or grade point average -"characteristics of students" becomes a list of specific characteristics such as age, sex, socioeconomic status, etc. B.Data to be collected are indicated; variables (characteristics) are indicated in measurable terms

CHARACTERISTICS OF PROPERLY STATED OBJECTIVES (continued) 3.If objectives take the form of research hypotheses to be tested, then: Hypothesis --tentative solution to a problem or answer to a question --conjectural statement of the relationship between two or more variables --specifies the relationship expected between variables

CHARACTERISTICS OF PROPERLY STATED OBJECTIVES (continued) 3. Research hypothesis (continued) A. A declarative sentence stating a relationship between variables B.The variables being treated as independent variables and dependent variables are identified C. How the variables are related (direction or nature of the relationship) is specified D. Supported by a rationale, that is there is some basis for the hypothesized expected relationships.

Basis (Rationale) for Hypotheses THEORY H Systematic ordering of ideas... to be able to interrelate a set of variables or characteristics on the basis of the rules of logic H Provides logical explanations for facts

THEORY (continued) A theoretical framework for research H Sharpens research objectives, questions or hypotheses H Suggests what variables or characteristics should be investigated H Aids in interpreting results H Makes the research cumulative from one study to the next Basis (Rationale) for Hypotheses (continued)

THEORY (continued) Deducing hypotheses (objectives or questions) from theory H Researcher proceeds in logical fashion from established facts and relationships to the formulation of new hypotheses (objectives or questions) to be examined empirically Basis (Rationale) for Hypotheses (continued)

Research and Null Hypotheses Research Hypotheses  Scientific hypotheses; substantive hypotheses  Derived from theory, related research or logical argument  Hypotheses stated in the proposal are research hypotheses

Research and Null Hypotheses (continued) Null Hypotheses  Statistical Hypotheses  Hypothesis of no difference or no relationship  Not stated in the proposal; used in the report of research when data are presented and statistical analysis is reported

Theory Related Research Logical Argument

Theory Related Research Logical Argument Hypotheses

Theory Related Research Logical Argument Hypotheses Test

Theory Related Research Logical Argument Hypotheses Test Confirmation or Disconfirmation of Hypotheses

Theory Related Research Logical Argument Hypotheses Test Confirmation or Disconfirmation of Hypotheses Explanation (Theory)

Parameter (Real World) Condition Type I Error (Type I = alpha level; H 1 is accepted when H 0 true) (Probability =  ) Correct Decision (Probability = 1 -  ) Truth Type II Error (Type II = beta level; H 0 is accepted when H 1 true) (Probability =  ) Outcome of Hypothesi s Test Correct Decision (Probability = 1 -  Power of Test) Reject H 0 Retain H 0 H 0 trueH 0 false

Normal Curve Percent of Cases Under Portions of the Normal Curve % 13.59% 2.14%

One-Tailed Test  =.05 95% 5%

Two-Tailed Test  =.05 95% 2.5%

NULL HYPOTHESIS One-Tailed (Directional) Test The Research Hypothesis: (actually H 1 or H a in word form) "The Miller Remedial Reading Program for seventh- grade students will significantly improve reading comprehension scores on the Thomas Reading Test as compared to the conventional method." Then, given: X 1 = Miller Remedial Reading Program X 2 = Conventional Method  Average (mean) of the population of other trials

One-Tailed (Directional) Test (continued) Write hypotheses schematically: H 0 :  1 =  2 (or,  1 -  2 = 0) H 1 (or H a ) =  1 >  2 (Could also be written for other tail)

One-Tailed (Directional) Test (continued) One usually writes a Decision Rule (D.R.) like: If the t observed is greater than the t crit(  =.05, __df), then reject H 0 and accept H 1 ; however, if t obs is less then the t crit, then accept H 0 and reject H 1.

One-Tailed (Directional) Test (continued) 5% The D.R. is saying the following in graphic form: 95% t crit(  =.05, __df) Accept H o X2X2 Reject H 0

One-Tailed (Directional) Test (continued) If t obs falls into shaded area, then researcher would say (as per D.R.): 1.Reject H 0 2.Accept Ha and could say: 3.Groups are significantly different 4.Improbable that we could have gotten this result by chance 5.X 1 is significantly better than X 2

One-Tailed (Directional) Test (continued) If t obs falls to the left of the t crit, then the researcher would say (as per D.R.): 1.Accept H 0 2.Reject H a 3.Groups not significantly different 4.Probable that any difference is due to chance 5.X 1 is not significantly better than X 2

NULL HYPOTHESIS Two-Tailed (Nondirectional) Test The Research Hypothesis: (actually H 1 or H a in word form) "To determine which method, the Miller Remedial Reading Program or the conventional method, is most effective in improving scores of seventh-graders on the Thomas Reading Test." Then, given: X 1 = Miller Remedial Reading Program X 2 = Conventional Method

Two-Tailed (Nondirectional) Test (continued) Write hypotheses schematically: H 0 :  1 =  2 (or,  1 -  2 = 0) H 1 (or H a ) =  1 >  2 H 2 (or H a' ) =  1 <  2

Two-Tailed (Nondirectional) Test (continued) Write hypotheses schematically: H 0 :  1 =  2 (or,  1 -  2 = 0) H 1 (or H a ) =  1 >  2 H 2 (or H a' ) =  1 <  2 (Note: a' is read: "a" prime) or, H 1 or H 2 :    

One usually writes a Decision Rule (D.R.) like: If the t obs is greater than t crit(  =.05, __df), then reject H 0 and H 2 and accept H 1 ; if t obs is less than t crit (  =.05, df), then reject H 0 and H 1 and accept H 2 ; and if t obs is not less than lower t crit or higher than upper t crit, then accept H 0 and reject H 1 and H 2. Two-Tailed (Nondirectional) Test (continued)

In graphic form: “Area B” 2.5% “Area C”“Area A” X2X2

A B C If t obs falls into shaded "Area C", then: 1.Reject H 0 and H 2 2.Accept H a 3.Groups are significantly different 4.X 1 is significantly better than X 2 5.Improbable results due to chance Two-Tailed (Nondirectional) Test (continued)

A B C If t obs falls in shaded "Area A", then: 1.Reject H 0 and H 1 2.Accept H 2 3.Groups are significantly different 4.X 2 is significantly better than X 1 5.Improbable results due to chance

If t obs falls in "Area B", then: 1.Reject H 1 and H 2 2.Accept H 0 3.Groups are not significantly different 4.Probable that any difference is due to chance Two-Tailed (Nondirectional) Test (continued) A B C