Aperçu des sections
About the course
Module
Statistics
Level:
Master
Year of study:
2nd year
Term/ semester:
3rd semester
Unit:
Discovery
Credit:
1
Coefficient:
1
Format:
Lectures (a hybrid of online and face-to-face lectures)
Evaluation format:
End of term exam (100%)
Day, time, & location:
- Sunday: 14:00 pm to 15:00 pm in Amphi B
- Wednesday 12:00 pm to 13:00 pm in Amphi B
Lecturer:
Moustafa Amrate
Email:
moustafa.amrate@univ-biskra.dz
Course description
This course focuses on the analysis of quantitative data in the fields of Applied Linguistics and TEFL. In addition to reviewing basic concepts in the field of statistics, the course introduces students to the main statistical tests used to determine the existence and strength of a relationship between two or more variables. This includes the statistical tests examining the significance of a difference (e.g. Paired t-test, One-Way-ANOVA …etc) or a relationship (e.g. Pearson correlation, Spearman correlation). The course also includes practical face-to-face and online activities in which the students will practice their knowledge of the different concepts and mastery of the different statistical tests.
Prerequisites
A high school level of Mathematics.
Course objectives
By the end of this course, the student will be able to:
- Choose the appropriate statistical test for the Master’s research project.
- Use the relevant statistical test for their research manually or by using Excel, or SPSS
- Interpret the results generated through the different statistical tests.
Lecture 2: Levels of measurement
Levels of measurement
Part 1 Part 2
Lecture 5: Applications of Descriptive Statistics
Descriptive Statistics in Excel
Calculating Descriptive Statistics in SPSS
Lecture 6: Introduction to Inferential Statistics and Hypothesis Testing
Inferential statistical tests in SPSS
The following table contains Youtube video tutorials demonstrating the necessary steps for conducting the different inferential statistical tests on SPSS.
PARAMETRIC TESTS
EQUIVALENT NON-PARAMETRIC TESTS
Paired t-test
Wilcoxon Rank sum test
Independent t-test
Mann-Whitney U test
ANOVA (One way analysis of variance)
Kruskal Wallis Test
Repeated measures ANOVA
Friedman test
Lecture 8: Correlation
Correlation analysis in SPSS
Pearson correlation
Spearman rank order correlation
References and extra resources
References
Dörnyei, Zoltán. (2007). Research methods in applied linguistics. Oxford university press.
Field, Andy. (2013). Discovering statistics using IBM SPSS statistics. sage.
Mackey, A., & Gass, S.M. (2015). Second Language Research: Methodology and Design (2nd ed.). Routledge. https://doi.org/10.4324/9781315750606
McKinley, J., & Rose, H. (Eds.). (2019). The Routledge handbook of research methods in applied linguistics. Routledge.
STATISTICAL SYMBOLS
The table below presents the most common symbols in statistics, their names, and their functions.
SYMBOL (NAME)
STATISTICAL FUNCTION
SAMPLE
POPULATION
Sample/ population size
n
N
Sum
Σ (sigma)
Mean
x̄ (x bar)
μ (mu)
Variance
S2 (s squared)
σ2 (sigma squared)
Standard deviation
S
σ (sigma)
Statistical probability
P (p value)
Pearson correlation
r
P
Spearman correlation
P or rs
Null hypothesis
H0
Alternative hypothesis
Ha