# Statistics I

15 ECTS credits

The course comprises the following five sections:

-Descriptive Statistics: This section covers methods for calculating different summary measures for the position and distribution of data material, as well as methods for describing connections between variables, including linear regression. The section also covers methods for collecting data and illustrating it graphically.

-Probability Theory and Random Variables: This section introduces students to the concept of probability, calculation laws for probability, discrete and continuous random variables, expectation value and variance. The section covers discrete distributions, primarily binomial, Poisson, and hypergeometric distribution. The continuous distributions covered are unimodal distribution, exponential distribution, T distribution, and normal distribution.

-Sampling Distribution: This section covers the way in which estimation of a quantity, for instance proportion, varies randomly between samples from the same population. This section provides a foundation for the following sections of the course.

-Point and Interval Estimation: This section gives students an introduction to properties of point estimates of mean values and proportions. Students are also taught how to construct and interpret confidence intervals.

-Introduction to Hypothesis Testing: This section will introduce a number of central concepts in hypothesis testing.

-Descriptive Statistics: This section covers methods for calculating different summary measures for the position and distribution of data material, as well as methods for describing connections between variables, including linear regression. The section also covers methods for collecting data and illustrating it graphically.

-Probability Theory and Random Variables: This section introduces students to the concept of probability, calculation laws for probability, discrete and continuous random variables, expectation value and variance. The section covers discrete distributions, primarily binomial, Poisson, and hypergeometric distribution. The continuous distributions covered are unimodal distribution, exponential distribution, T distribution, and normal distribution.

-Sampling Distribution: This section covers the way in which estimation of a quantity, for instance proportion, varies randomly between samples from the same population. This section provides a foundation for the following sections of the course.

-Point and Interval Estimation: This section gives students an introduction to properties of point estimates of mean values and proportions. Students are also taught how to construct and interpret confidence intervals.

-Introduction to Hypothesis Testing: This section will introduce a number of central concepts in hypothesis testing.

Progressive specialisation:
G1N (has only upper‐secondary level entry requirements)

Education level:
Undergraduate level

Admission requirements:
- field-specific eligibility A4 (upper secondary school level Mathematics 3b or 3c, Civics 1b or 1a1 + 1a2), barring Civics 1b or 1a1 + 1a2, or
- field-specific eligibility 4 (upper secondary school level English B, Mathematics C, Civics A) barring English B and Civics A.

Selection:

Selection is usually based on your grade point average from upper secondary school or the number of credit points from previous university studies, or both.