Psyf 568 master syllabus agosto08

MASTER SYLLABUS PSYF-568

CARLOS ALBIZU UNIVERSITYSAN JUAN CAMPUS

MASTER SYLLABUSPSYF-568: APPLIED INFERENTIAL STATISTICS

CREDITS: 3 CONTACT HOURS: 45

COURSE DESCRIPTION

The course offers an introduction to inferential statistics in the context of psychological research. The topics covered include: hypothesis testing, statistical inference and research, probability theory, sampling distributions, parametric and non-parametric statistical tests, the normal curve, t and F distributions, Chi square, and the Mann-Whitney’s U test, among others.

PRE-REQUISITES

The course requires that the student have previous knowledge of basic statistical concepts, including descriptive statistics.

COURSE OBJECTIVES

The course is intended to empower students with knowledge about inferential statistics and methodology pertaining to psychological research; to enable the student to differentiate among the statistical methods available for hypothesis testing, to evaluate the advantages and disadvantages of such methods, to properly apply inferential statistical procedures with actual research data, and to read and interpret inferential statistical results. Furthermore, the course is intended to help students have a better comprehension of which statistical analysis to utilize when minority populations are assessed.

REQUIRED TEXT BOOKS

Runyon, R.P., Coleman, K.A., & Pittenger, D.J. (2000). Fundamentals of behavioral statistics (9th ed.). Boston, MA: McGraw Hill.

Sánchez-Viera, J.A. (2004). Fundamentos del razonamiento estadístico (3rd ed., revisada). San Juan, PR: Universidad Carlos Albizu.

Page 1 of 13


ITINERARY OF CLASS UNITS

Unit 1: Introduction to statistical inference conceptsUnit 2: Introduction to hypothesis testingUnit 3: Sampling and sampling distributionsUnit 4: Use of normal distribution for determining probabilities Unit 5: Inferential statistics for single-group research designs Unit 6: First Partial ExamUnit 7: Inferential statistics for (within-group) repeated-measures research

Designs: contrasting means and variancesUnit 8: Inferential statistics for (within-group) repeated-measures research

designs: Chi square for non-parametric testsUnit 9: Inferential statistics for (within-group) repeated-measures research

designs: Wilcoxon’s T and simple One Way ANOVA)Unit 10: Second Partial ExamUnit 11: Inferential statistics for (between-group) independent samples

research Designs: Contrasting means and proportionsUnit 12: Inferential statistics for (between-group) independent samples

research designs: Mann Whitney’s U and one way ANOVA for independent groups

Unit 13: Inferential statistics for correlational research designsUnit 14: Final Exam

COURSE CONTACT HOURS

Professors who teach the course must divide the contact hours the following way:

1. Face-to-face time in the classroom must not be less than 40 hours (16 classes, 2.5 hours each class).

2. For the remaining hours (>5 hours), students will conduct research projects or homework outside the classroom. These projects or homework will include, but are not limited to, practice exercises and assignments to do as homework and hand in for credit.

METHODOLOGY

The professor who offers the course will select the specific methodology. Teaching methodology for this course can include, among others: conferences by the professor, group discussions, class research projects, in-classroom and assigned problems and exercises involving real and hypothetical research data and situations.

Page 2 of 13


EDUCATIONAL TECHNIQUES

The professor who offers the course will select the specific educational techniques. The techniques could include, but will not be limited to: practical demonstrations, providing printed materials (handouts), slide shows and simulations, among others.

EVALUATION

The professor who offers the course will select the specific evaluation criteria. These criteria could include, but would not be limited to: projects, exams, class presentations, homework assignments, and exercises.

RESEARCH COMPETENCIES

1. Utilizing inferential statistics to develop and evaluate research hypotheses in various research designs.

2. Performing statistical analyses that are relevant to the evaluation of research hypotheses in the context of various research designs.

3. Presenting and interpreting the results of inferential statistical analyses competently.

ATTENDANCE POLICY

Class attendance is mandatory for all students. After two unexcused absences, the student will be dropped from the class, unless the professor recommends otherwise. When a student misses a class, he/she is responsible for the material presented in class.

AMERICANS WITH DISABILITIES ACT (ADA)

Students that need special accommodations should request them directly to the professor during the first week of class.

Page 3 of 13


COURSE UNITS

UNIT 1: INTRODUCTION TO STATISTICAL INFERENCE CONCEPTS

Upon completion of this unit, students will understand the basic concepts pertaining to statistical inference, as well as the role of inferential statistics in behavioral research.

LEARNING OBJECTIVES:

Upon successful completion of this unit, students will be able to:

1. Distinguish between inferential and descriptive statistics2. Discuss the role of statistical inference in behavioral research3. Identify the limitations of statistical inference in behavioral research

ASSIGNED READINGS:

Sánchez-Viera (2004) Chapter 1 – Introducción (Introduction) Chapter 10 - Inferencia estadística (Statistical Inference)

Runyon, Coleman & Pittenger (2000) Chapter 11 – Introduction to statistical inference

UNIT 2: INTRODUCTION TO HYPOTHESIS TESTING

Upon completion of this unit, students will understand the concepts and process of hypothesis testing, as well as describe the steps involved in scientific hypothesis testing.



1. Identify the steps associated with hypothesis testing in psychological research and in assessment and diagnosis of ethnic minority clients.

2. Discuss the concepts of research hypothesis and statistical hypothesis3. Distinguish between Type I and Type II errors4. Explain the concepts of significance level and statistical power5. Discuss the concept of one-tailed vs. two-tailed tests in relation to research

hypotheses.6. Discuss the basic concepts of probability theory in its relation to statistical

inference

Page 4 of 13


REQUIRED READINGS:

Sánchez-Viera (2004) Chapter 10 - Inferencia estadística (Statistical Inference)

UNIT 3: SAMPLING AND SAMPLING DISTRIBUTIONS

Upon completion of this unit, students will understand the concepts of sampling and sampling distributions in psychological research and in assessment of minority populations.



1. Explain the concept of sampling distribution2. Identify different types of sampling distributions commonly used in statistical

tests3. Discuss the theory underlying sampling distributions4. Understand the use of probability models in statistical tests5. Describe different sampling methods and their differences6. Explain the concept of sampling error

ASSIGNED READINGS:

Sánchez-Viera (2004) Chapter 17 – Sobre muestras y muestreo: Nociones Basicas (On samples

and sampling: Basic concepts)

Runyon, Coleman & Pittenger (2000) Chapter 11 – Introduction to statistical inference (pp. 266-277)

Section 11.3 – The concept of sampling distributionsSection 11.4 – Applications of the sampling distribution

Page 5 of 13


UNIT 4: USE OF THE NORMAL DISTRIBUTION FOR DETERMINING PROBABILITIES

Upon completing this unit, students will acquire knowledge about the normal distribution, its characteristics and its use to determine probabilities and test for significance.


Upon completion of this unit, students will be able to:

1. Explain the characteristics of the normal distribution.2. Use the normal distribution to determine probabilities.3. Define the concepts of “probability”, “sampling distribution”, “normal curve”. 4. Determine probabilities using the formula (Z) as a significance test.

ASSIGNED READINGS:

Sánchez-Viera (2004) Chapter 11 – La curva normal: Teoría y aplicaciones (The normal curve:

Theory and applications)

UNIT 5: INFERENTIAL STATISTICS FOR SINGLE-GROUP RESEARCH DESIGNS

Upon completion of these units, students will understand the process of statistical inference with one-sample research designs, as well as the appropriate use of these tests for behavioral research, including: normal distribution, t-test, and Chi square.


Upon successful completion of these units, students will be able to:

1. Discuss the assumptions of statistical tests for single-group research designs2. Identify real and hypothetical research situations where these designs are

applicable3. Identify the limitations of statistical tests for single-group research designs4. Compute statistics for the comparison of sample vs. population means using

the normal and the Student-t distributions.5. Compute statistics for the comparison of sample vs. population proportions

using the normal distribution.6. Solve one-sample statistical tests through the Chi square distribution to

compare sample vs. population variances.

Page 6 of 13


7. Solve one-sample statistical tests through the binomial distribution to compare sample vs. population proportions.

8. Competently interpret results from single-group statistical tests

ASSIGNED READINGS:

Sánchez-Viera (2004) Chapter 11, section 11.5 – Diseño de una muestra: Contraste de medias

(Single-group research design: Contrasting means) Chapter 11, section 11.7 - Diseño de una muestra: Contraste de

proporciones (Single-group research design: Contrasting proportions) Chapter 12, section 12.3 – Diseño de una muestra: Contraste de medias

(Single-group research design: Contrasting means) Chapter 13, Section 13.2 – Chi cuadrado para contrastes de varianzas:

Diseño de una muestra (Chi Square for comparing variances: Single-group research designs

Chapter 13, Section 13.3 – Aplicaciones de Chi cuadrado en pruebas noparametricas (Applications of Chi square for non-parametric tests)

Chapter 14, section 14.4 – Diseño entre grupos: Prueba H de Kruskal=Wallis (Independent group research designs: Kruskal-Wallis H test)

Runyon, Coleman & Pittenger (2000) Chapter 12 – Statistical inference: Single samples

UNIT 6: FIRST PARTIAL EXAM

UNIT 7: INFERENTIAL STATISTICS FOR (WITHIN-GROUP) REPEATED-MEASURES RESEARCH DESIGNS: CONTRASTING MEANS AND VARIANCES

Upon completion of this unit, students will understand the processes of inferential statistics for correlated-samples (repeated-measures) research designs. Students will discuss the applications and proper use of these tests in psychological research, including: t-test, Chi Square, normal distribution, Wilcoxon’s T.



1. Discuss the assumptions of statistical tests for (within-group) repeated-measures research designs.

Page 7 of 13


2. Identify real and hypothetical research situations where these tests are applicable

3. Identify the limitations of statistical tests for repeated-measures research designs

4. Compute statistics for the comparison of correlated-samples’ means, and variances using the Student-t distribution.

5. Compute statistics for the comparison of correlated-samples’ means, and variances using the normal distribution.

ASSIGNED READINGS:

Sánchez-Viera (2004) Chapter 12, section 12.4 – Diseño intragrupos: Contraste de medias

(Within-group research designs: Comparing means) Chapter 12, section 12.9 – Diseño intragrupos: Contraste de 2 varianzas

(Within-group research designs: Comparing variances)

Runyon, Coleman & Pittenger (2000) Chapter 13 – Statistical inference: Two-sample cases

UNIT 8: INFERENTIAL STATISTICS FOR (WITHIN-GROUP) REPEATED-MEASURES RESEARCH DESIGNS: CHI SQUARE FOR NON-PARAMETRIC TESTS

Upon completion of this unit, students will understand the processes of inferential statistics for correlated-samples (repeated-measures) research designs. Students will discuss the applications and proper use of these tests in psychological research, including Chi Square.



1. Perform correlated–sample statistical tests through the Chi square distribution to compare proportions in repeated measures designs.

2. Competently interpret and present the results from statistical tests for repeated-measures research designs, including Chi Square.

ASSIGNED READINGS:

Sánchez-Viera (2004) Chapter 13, section 13.3 – Aplicaciones de Chi Cuadrado en pruebas no

paramétricas (Chi square for non-parametric tests)

Page 8 of 13



UNIT 9: INFERENTIAL STATISTICS FOR (WITHIN-GROUP) REPEATED-MEASURES RESEARCH DESIGNS: WILCOXON’S T AND SIMPLE ONE WAY ANOVA

Upon completion of this unit, students will understand the processes of inferential statistics for correlated-samples (repeated-measures) research designs. Students will discuss the applications and proper use of these tests in psychological research, including: Wilcoxon’s T and the F statistic.



1. Discuss the assumptions of statistical tests for (within-group) repeated-measures research designs.


3. Perform correlated samples statistical tests using the Wilcoxon’s T test and the signs test.

4. Perform correlated samples statistical tests using the F statistic 5. Competently interpret results from statistical tests for repeated-measures

research designs, including the signs test, Wilcoxon’s T and the F statistic.

ASSIGNED READINGS:

Sánchez-Viera (2004) Chapter 14, section 14.6 – Diseño intragrupos: Prueba de los signos

(Within group research designs: the signs test) Chapter 14, section 14.7 – Diseño intragrupos: Prueba T de Wilcoxon

(Within group research designs: Wilcoxon’s T test) Chapter 15, Section 15.7 – Análisis de varianza simple para un diseno

intragrupos (Simple oneway ANOVA for within-group research designs)

Runyon, Coleman & Pittenger (2000) chapter 13 – Statistical inference: Two-sample cases Chapter 18 (section 18.3) – Statistical inference: Ordinally scaled

variables

UNIT 10: SECOND PARTIAL EXAM

Page 9 of 13


UNIT 11: INFERENTIAL STATISTICS FOR (BETWEEN-GROUP) TWO INDEPENDENT SAMPLES RESEARCH DESIGNS: CONTRASTING MEANS AND PROPORTIONS

Upon completion of these units, students will understand the processes of statistical inferences for designs with two independent samples (between group designs), as well as the appropriate use of these tests in psychological research, including: the normal distribution, t-test, Chi Square and Mann-Whitney’s U test.



1. Discuss the assumptions of statistical tests for between-group research designs


3. Identify the limitations of statistical tests for research designs comparing two independent samples.

4. Compute statistics for the comparison of two independent samples’ means and proportions using the Student–t distribution.

5. Compute statistics for the comparison of two independent samples’ means and proportions using the normal distribution.

6. Solve independent–samples statistical tests through the Mann-Whitney’s U test (for variables in ordinal scale).

7. Solve independent–samples statistical tests through the Chi-square distribution (tests of independence, median test, etc.).

8. Competently interpret results from statistical tests for two-independent-samples research designs.

ASSIGNED READINGS:

Sánchez-Viera (2004) Chapter 11, Section 11.6 - Diseño entregrupos: Contrastes para 2 medias

muestrales (Independent samples research designs: comparing means) Chapter 11, Section 11.8 - Diseño entregrupos: Contrastes para 2

proporciones muestrales (Independent samples research designs: comparing proportions)

Chapter 12, section 12.5 – Diseño entregrupos: Contrastes para 2 medias muestrales (Independent samples research designs: comparing means)

Chapter 12, Section 12.8 – Diseño entregrupos: Contrastes para 2 proporciones muestrales (Independent samples research designs: comparing proportions)


Page 10 of 13


UNIT 12: INFERENTIAL STATISTICS FOR (BETWEEN-GROUP) TWO INDEPENDENT SAMPLES RESEARCH DESIGNS: MANN WHITNEY’S U AND ONE WAY ANOVA FOR INDEPENDENT GROUPS

Upon completion of this unit, students will understand the processes of statistical inferences for designs with two independent samples (between-group designs), as well as the appropriate use of these tests in psychological research, including Mann-Whitney’s U test and one way ANOVA.



1. Perform independent–samples statistical tests using the Mann-Whitney’s U test (for variables in ordinal scale).

2. Perform independent–samples statistical tests using the Chi-square distribution (tests of independence, median test, etc.).

3. Perform independent–samples statistical tests using oneway ANOVA for comparing means.

4. Competently present and interpret results from statistical tests for two-independent-samples research designs, including Mann-Whitney’s U and oneway ANOVA.

ASSIGNED READINGS:

Sánchez-Viera (2004) Chapter 14, section 14.3 – Diseño entregrupos: Prueba U de Mann-

Whitney (Independent samples research designs: Mann-Whitney’s U test ) Chapter 15, section 15.5 – Análisis de varianza simple para un diseño

entregrupos (Simple oneway ANOVA for between-group research designs)

Chapter 15, section 15.8 – Contrastes de varianzas para muestras independientes (Comparing variances in between-group research designs)


Page 11 of 13


UNIT 13: CORRELATIONAL STATISTICS

Upon completion of this unit, students will understand the process through which correlation coefficients are computed and tested for significance, as well as the different statistical methods available and their significance tests.



1. Discuss the assumptions of statistical tests for correlation coefficients2. Identify the different methods through which correlation coefficients can be

tested for significance (normal curve, t-test, chi square, tables of critical values, etc.) and their applications.

3. Compute correlation coefficients for interval- and ratio- scaled variables (Pearson’s r)

4. Competently interpret results from statistical tests for correlational analysis

ASSIGNED READINGS:

Sánchez-Viera (2004) Chapter 9 – Correlación y regresión simple lineal (Correlation and simple

linear regression) Chapter 16- Pruebas de hipótesis para índices de correlación (tests of

significance for correlation indexes)

Runyon, Coleman & Pittenger (2000) Chapter 8 - Correlation

UNIT 14: FINAL EXAM

Page 12 of 13


REFERENCES

Bordens, K.S., & Abbot, B.B. (1991). Research design and methods: A process approach (2nd ed.). California: Mountain View.

Champion, H. (1981). Basic statistics for social research (2nd ed.). New York: McMillan.

Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155-159.

Diekhoff, G.M. (1996). Basic statistics for the social and behavioral sciences. New Jersey: Prentice Hall.

Goodwin, C.J. (1995). Research in psychology: Methods and design. New York: John Wiley and Sons.

Hays, W.L. (1981). Statistics (3rd ed.). New York: Holt, Rinehart & Winston.

Hernández-Sampieri, R., Fernández-Collado, C., & Baptista-Lucio, P. (1991). Metodología de la investigación (2da ed.). México: McGraw-Hill.

Kerlinger, F., & Lee, H. (2002). Investigación del comportamiento (4ta ed.). México: McGraw-Hill.

Malgady, R.G. (1996). The question of cultural bias in assessment and diagnosis of ethnic minority clients: Let’s reject the null hypothesis. Professional Psychology: Research and Practice, 27 (1), 79-77.

Ritchey, F. J. (2002). Estadística para las ciencias sociales: El potencial de la imaginación estadística. México: McGraw Hill.

Rosenthal, R., & Rosnow, R.L. (1991). Essentials of behavioral research: Methods and data analysis (2nd ed.). New York: McGraw-Hill.

Runyon, R.P., Coleman, K.A., & Pittenger, D.J. (2000). Fundamentals of behavioral statistics (9th ed.). Boston, MA: McGraw Hill.

Sánchez-Viera, J.A. (2004). Fundamentos del razonamiento estadístico (3ra ed., revisada). San Juan, PR.: Universidad Carlos Albizu.

Visauta-Vinacua, B. (1997). Análisis estadístico con SPSS para Windows: Estadística básica. México: McGraw Hill.

Vogt, P.W. (1999). Dictionary of statistics and methodology (2nd ed.). Thousand Oaks, CA: Sage.

Revised by: María C. Vélez-Pastrana, Ph.D. (December, 2000; October, 2003)Revised by: Sean K. Sayers Montalvo, Ph.D. (June, 2006)Revised by: María C. Vélez-Pastrana, Ph.D. (August, 2008)

Page 13 of 13

Technology

Psyf 568 master syllabus agosto08