Introduction to Descriptive and Inferential Statistics

Course Description  

This course is an introduction to descriptive and inferential statistics, which are useful for describing and analyzing data from a variety of fields. The topics covered include: analysis of univariate and bivariate data (including frequency distributions and graphs, measures of central tendency and variability, covariance and correlation), probability and random variables, sampling distributions, point and confidence interval estimation, and hypothesis testing (onesample and two-sample tests of hypothesis for means, variances and proportions, Wilcoxon signed-rank test, Wilcoxon-Mann-Whitney Test, and chi-square tests). The statistical package SPSS will be used in this course.  

 

Course Goals  

This course seeks to provide students with a better understanding of statistics in the context of applied research. In particular, this course aims to:  

• Introduce students to statistical techniques of data analysis. • Increase students’ awareness of the applicability of these statistical techniques to reallife cases.

• Enable students to choose the most appropriate statistical method for a data analysis problem.  

• Enable students to interpret and report the results of the statistical procedures covered in this course.

• Introduce students to the use of SPSS computer software for statistical analysis. 

 

Course Materials  

Textbooks are not required for this course.  All necessary materials will be provided on the course website.  Complementary Bibliography  - Shafer D.S. and Zhang Z. (2012). Beginning Statistics. Creative Commons  

 

Course Requirements and Grading

Your final grade will be calculated as follows:

• Class participation: 10%.

• In-class presentations: 40%

• Mid-term exam: 20%.

• Final exam: 30% Exams and every other assignment will be marked following the Spanish numerical range. 

 

Course Contents

Unit 1. Descriptive statistics.

1.1. Basic concepts and definitions.  

1.2. Analysis of univariate data: frequency distributions and graphs.

1.3. Analysis of univariate data: measures of central tendency.

1.4. Analysis of univariate data: measures of variability.

1.5. Analysis of bivariate data: joint frequency distributions, graphs, covariance, and correlation.  

Unit 2. Probability and random variables.

2.1 Probability

2.2 Conditional probability and independence of events.  

2.3 Random variables.

2.4 Discrete univariate random variables: expectation, variance, probability mass function, and cumulative distribution function.

2.5 Continuous univariate random variables: expectation, variance, probability density function, and cumulative distribution function.

Unit 3. Statistical inference.

3.1 Population and samples.

3.2 Sampling distributions.

3.3 Point estimation.

3.4 Interval estimation.

3.5 Hypothesis testing: parametric and non-parametric tests.