## Tags

Y1

## Admissions requirements

None, this is a compulsory Year 1 course for all first-year LUC students.

## Description

This course gives an introduction to the basic concepts and techniques of statistical inference. Students will learn the basic principles of data collection, and how to explore patterns in data by means of descriptive statistics and graphs. It provides an introduction to the quantitative analysis of data by means of point estimates, confidence intervals, statistical tests on means, and regression analysis.

In addition, the course gives an introduction to programming in R, and the use of this software for statistical analysis.

## Course objectives

Skills

After successful completion of this course students should be able to:

Examine patterns in data graphically and quantitatively;

Relate the mode, median, mean, variance, standard deviation, and skewness, to the shape of a distribution;

Formulate and test hypotheses on the mean of a single population, and interpret the outcomes.

Formulate and test hypotheses on the means of two populations, and interpret the outcomes.

Perform a simple linear regression analysis and be able to interpret the results.

Write simple programs in R

Use R for statistical analysis

Knowledge

After successful completion of this course students should know and understand the following concepts and techniques:

Mode, median, mean, variance, standard deviation, and skewness

Histogram, Boxplot

Normal distribution, Student-t distribution, Z-score

Null hypothesis, alternative hypothesis

test statistic, p-value, significance level, critical values, type-1 error, type-2 error

confidence interval, confidence level, relation between confidence interval and hypothesis test, margin of error

Simple linear regression, regression parameters, residuals, correlation coefficient, outliers, residual plot

R code for working with variables, arrays, and dataframes, ‘for’-loops, computing (summary) statistics, making scatter plots and histograms, simple linear regression, importing data, installing and loading packages

## Timetable

Once available, timetables will be published here.

## Mode of instruction

Lectures, group discussion and -assignments, and computer labs with R.

## Assessment

In-class participation: 5%

Quizzes: 30% (weeks 2 to 7)

R-coding exam, on laptop 25% (week 7)

Final, written exam: 40% (Reading week)

## Blackboard

There will be a Blackboard site available for this course. Students will be enrolled at least one week before the start of classes.

## Reading list

Open Intro Statistics, 2015 (3rd edition)

By: David M. Diez, Christopher D. Barr, Mine Çetinkaya-Rundel

This textbook can be downloaded for free at the website: www.openintro.org.

**Please make sure you download the right book!**

## Registration

This course is open to LUC students and LUC exchange students. Registration is coordinated by the Education Coordinator. Interested non-LUC students should contact course.administration@luc.leidenuniv.nl.

## Contact

Dr. P. Haccou (convener)

p.haccou@luc.leidenuniv.nl