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# Statistics and social science methodology

This is the study programme for 2019/2020. It is subject to change.

An introduction to different research designs, quantitative and qualitative. An introduction to simple methods for collecting, analyzing and presenting data. An introduction to basic probability theory and standard probability distributions. An introduction to estimations, confidence intervals and hypothesis testing. An introduction to linear regression analysis and correlations. Use of software.

### Learning outcome

After completion of the course, the student are expected to have attained the following knowledge, skills and general competences:
Knowledge:
The student will
• Have insight in various research designs, quantitative and qualitative
• Know of different data collection methods, quantitative and qualitative
• Know how to interpret descriptive statistics
• Have basic knowledge about probability theory, conditional probability, random variables, expectations and variance, important probability distributions and the central limit theorem
• Have basic knowledge of point estimation, confidence intervals and hypothesis testing, know of p-values and know how to calculate the power of a hypothesis test and its sample size
• Have basic knowledge of methods for data analysis, such as correlation, two sample tests, quadratic tests and simple linear regression analysis
• Know key requirements for casual explanations in social sciences.

Skill
The student will
• Be able to use basic methods to presentation of data
• Master basic probability theory
• Be able to calculate the expectation, the variation and probabilities of random variables and simple functions of random variables
• Be able to use basic probability distributions, such as the Binomial, the Poisson, the hypergeometric and the normal distribution
• Be able to estimate and calculate confidence intervals for central parameters of basic probability distributions
• Be able to define research questions and perform hypothesis testing in certain simple situations
• Be able to perform simple correlation- and regression analysis
• be able to assess whether causal explanations satisfy common requirements
• Be able to make basic data analyses using relevant software
• Have the necessary understanding of statistics needed to be able to read professional literature that pertains to their field of study

General competence
The student will
• Be able to obtain relevant answers to academic founded questions through the use of statistical surveys and methods
• Understand statistical thinking and methodology
• Understand different methods used to obtain qualitative data
• Be able to critically evaluate the execution and presentation of statistical surveys

### Contents

The course is a standard first course in statistics covering the following topics:
An introduction to simple methods for collecting, analyzing and presenting data. An introduction to basic probability theory, including concepts such as conditional probability, expectation, and variance and an introduction to common probability distributions such as binomial,hypergeometric, Poisson and normal distribution. An introduction to point estimation, confidence intervals, and hypothesis testing in situations with one or two selections, as well as the chi-squared distribution test. An introduction to linear regression analysis and correlation. An introduction to various research designs, quantitative and qualitative. Use of software.

None.

### Recommended previous knowledge

BØK135 Mathematical analysis for economy and social science

### Exam

Weight Duration Marks Aid

### Coursework requirements

Fem obligatoriske innleveringer, hvorav to er dataøvinger
Five mandatory assignment of which two consists of data analysis with statistical software and three are on theoretical matters. A least four of the five mandatory assignments has to have been approved, including both of the data analysis assignments, in order to be permitted to write the exam.

### Course teacher(s)

Course teacher
Stein Andreas Bethuelsen
Course coordinator
Tore Selland Kleppe

### Method of work

Five hours of lectures and two hours of group work every week. The mandatory hand-ins have to be approved in order to take the final exam.
The total workload expected of the student is 250-300 hours.

### Overlapping courses

Course Reduction (SP)
Introduction to Probability and Statistics (ÅMA110_1) 5
Mathematics and statistics (BØK160_1) 5
Introduction to probability and statistics (TE0199_1) 5
Introduction to probability and statistics (TE0199_2) 5
Introduction to probability and statistics (TE0199_A) 5
Statistics for economists (ØK0061_1) 5
Statistics for economists (ØK0061_A) 5
Mathematics, method and statistics (BRL100_1) 5
Mathematics, method, statistics and epistemology (BRL100_2) 5
Statistics and research methods (BHO115_1) 5
Statistics (BØK145_1) 5
Introduction to probability and statistics 1 (BMF100_1) 8
Probability and Statistics 1 (STA100_1) 8
Qualitative and quantitative methods (BPS310_1) 10

### Open to

Accounting and Auditing - Bachelor's Degree Programme
Sociology - Bachelor's Degree Programme
Political Science - Bachelor's Degree Programme