Information Package
baskent.edu.tr

Program of Sociology (English)

SOCI215

BASIC STATISTICS

Course Code
SOCI215
Semester
Third Term (Fall)
Theory+Practice
3 + 0
ECTS
4
Course TypeCompulsory Course
Course LevelBachelor's Degree
Year of Study2
SemesterThird Term (Fall)
ECTS4
Name of Lecturer(s)
Learning Outcomes

At the end of this course, the students;

  1. Define and summarize the basic terms and/or concepts used in statistics.
  2. Explain statistical reasoning.
  3. Visualize data properly.
  4. Distinguish and apply the appropriate statistical techniques for data.
  5. Express reasonably complete interpretations of the analyses.
  6. Make predictions and inferences by evaluating the results of analyses.
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme ComponentsNo
Course DescriptionThe aim of this course is to teach basic statistics concepts and basic statistical methods.
Course Contents
WEEK TOPICS
1st Week Statistics: What it is (and isn't)
2nd Week Descriptive statistics, Measures of central tendency: Mean, median, and mode
3rd Week Measures of variability: Range, variance, and standard deviation
4th Week Why illustrates data?, Creating a frequency distribution, Creating a histogram the Tally- Ho method, Bar charts, Line charts, Pie charts, The frequency polygon, Cumulating frequencies, Average value, Variability, Skewness, Kurtosis
5th Week Correlation coefficients, What are correlations all about?, Types of correlation coefficients, Computing a simple correlation coefficient, A visual picture of correlation: The scatterplot, The correlation matrix, Squaring the correlation coefficient, Association Versus Causality, Other correlations
6th Week Measurement and scales: Nominal, ordinal, interval, and ratio, Reliability, Test scores, Observed score, Different types of reliability, Interpreting reliability coefficients, Validity, Different types of validity
7th Week Hypotheticals, Population and Sample, The null hypothesis: The purpose of null hypothesis, The research hypothesis, The nondirectional research hypothesis, The directional research hypothesis, Differences between the null hypothesis and the research hypothesis, What makes a good hypothesis?
8th Week Midterm exam
9th Week Probability, The normal curve (aka the bell- shaped curve), z Scores: What z Scores represent, Hypothesis testing and z Scores
10th Week The concept of significance, Significance versus meaningfulness, An introduction to inferential statistics, How inference works, How to select what test to use, How to use the chart, An introduction to tests ofsignificance, How a test of significance works: The plan, Confidence intervals
11th Week The one-sample z-Test, Computing the Test Statistics, Tests between the means of different groups: Introduction to the t-Test for independent samples, Computing the Test Statistics, Computing and understanding an effect size, Tests between the means of related groups: Introduction to the t-Test for dependent samples, Computing the test statistics
12th Week Analysis of Variance (ANOVA), Different flavors of ANOVA, Computing the F-test statistics, Factorial Analysis of Variance and computing the test statistics
13th Week Using linear regression, What is the prediction all about?, The logic of prediction, Using data analysis tools to compute the regression equation
14th Week Chi-Square: Introduction to nonparametric statistics, One-sample Chi-Square Computing and the Chi-Square test statistics
15th Week Other nonparametric tests and recap of the semester
Recommended or Required ReadingTemel İstatistik Yöntemleri, Yrd. Doç. Dr.Serpil Cula, Prof.Dr. Zehra Muluk, Başkent Üniversitesi
İşletme ve İktisatçılar İçin İstatistik, 4. Basımdan çeviri?,Literatür Yayıncılık, 2000
Sosyal Bilimler için İstatistik, Şener Büyüköztürk, Ömay Çokluk Bökeoğlu, Nilgün Köklü, Pegem Akademi, 2009
Sencer M.(1989), Toplum Bilimlerinde Yöntem, İstanbul: Beta Yayım Dağıtım A.Ş.
Çömlekçi, N.(1994), Temel İstatistik İlke ve Teknikleri, Ankara: Bilim ve Teknik Yayınevi.
Planned Learning Activities and Teaching Methods
  • Lecture
  • Discussion
  • Questions/Answers
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 30
Quiz 2 30
Total(%) 60
Contribution of In-term Studies to Overall Grade(%) 60
Contribution of Final Examination to Overall Grade(%) 40
Total(%) 100
ECTS Allocated Based on Student Workload
Activities Quantity Duration (Hour) Total Workload (Hour)
Midterm exam 1 2 2
Preparation for Quiz 0 0 0
Individual or group work 7 2 14
Preparation for Final exam 1 30 30
Course hours 14 3 42
Preparation for Midterm exam 1 20 20
Laboratory (including preparation) 0 0 0
Final exam 1 2 2
Homework 3 4 12
Total Work Load122
Total Work Load / 30 (h)4.06
ECTS Credit of the Course4
Language of InstructionEnglish
Work Placement(s)No

Programme Qualifications / Learning Outcomes

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K3 X X X
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K5 X X X X X X
K6 X X
K7 X X X X
K8 X X X X X X
K9 X X
K10 X
K11 X X X X
K12 X X X