Course

Statistics For Business and Economics (BØK356)

In the increasingly data-driven business environment, it is crucial for a modern business person to know how to utilize data. This course will teach you introductory statistics for business and economics students. The knowledge you acquire from this course will equip you with statistical literacy—a necessity to navigate through the digital world we live in today. Moreover, the fundamental knowledge in statistics and programming serves as the absolute basis for a deeper understanding of concepts such as DX (digital transformation), big data, machine learning, and artificial intelligence.


Dette er emnebeskrivelsen for studieåret 2021-2022

See course description and exam/assesment information for this semester (2024-2025)

Semesters

Fakta

Emnekode

BØK356

Vekting (stp)

10

Semester undervisningsstart

Spring

Undervisningsspråk

English

Antall semestre

1

Vurderingssemester

Spring

Timeplan

Vis timeplan

Litteratur

Pensumlisten finner du i Leganto

Content

Typical subject areas covered are:

  • Descriptive statistics
  • Probability
  • Combinatorics
  • Conditional probability
  • Random variables, mean, and variance
  • Joint distributions
  • Basic probability distributions
  • Estimation
  • Hypothesis testing
  • Linear Regression

 

Expectations: 280 ECTS work hours divided into lectures, learning sessions, computer (R programming) sessions, out-of-class work, exercises, and independent study.

Learning outcome

Knowledge

On completion of the course, students will gain knowledge in:

  • Utilizing fundamental statistical concepts, methods, and data to gain insights
  • Basic programming in R

 

Skills

Upon completion of this course, students will be able to:

 

  • Describe data using summary statistics
  • Approximate real-world events with appropriate random variables and probability distributions
  • Master basic probability theory and probability models, combinatorics, sampling models, conditional probability, Bayes law, and independence of random variables.
  • Conduct hypothesis testing in binomial and multinomial models
  • Depict the relationship between and among variables using statistics, such as correlation and regression analysis
  • Import and export data into R
  • Use R to construct different measures and variables
  • Use R to conduct basic statistical analysis

Forkunnskapskrav

Ingen

Exam

Form of assessment Weight Duration Marks Aid Exam system Withdrawal deadline Exam date
Written exam 1/1 4 Hours Letter grades One hand written A4-page with notes 1), Approved, basic calculator 2), Dictionary 3) Inspera assessment — —

1) A4-page handwritten notes. You can write on both sides
2) Pre approved calkulator
3) Norwegian-English, English-Norwegian dictionary

 The final grade is based on a final individual exam accounting for 100% of the grade.

Vilkår for å gå opp til eksamen/vurdering

, , Pass two individual quizzes

 

  • It is required that each group receive a “pass” for at least 5 group reflection notes to be admitted to the final exam.

 

  • Students are required to attend at least 8 of the learning sessions and 8 of the R sessions.

Fagperson(er)

Study Program Director:

Tarjei Mandt Larsen

Course coordinator:

Yuko Onozaka

Course teacher:

Sufyan Ullah Khan

Method of work

In this course, you will learn through a mixture of traditional lectures, instruction videos, learning sessions, R sessions, and individual study. Lectures provide the basic statistical concepts, while both learning and R sessions will be problem/project-based in interactive and collaborative settings. Both learning and R sessions are mandatory attendance of at least 8 sessions each. There will be exercises provided for each topic covered

Åpent for

Business Administration - Bachelor's Degree Programme
Exchange programmes at UIS Business School

Emneevaluering

Students will have the opportunity to give feedback on the course first in an early dialogue, and then in a written course evaluation at the end of the course.

Litteratur

Book

Introductory Statistics for Business and Economics [electronic resource] : Theory, Exercises and Solutions Ubøe, Jan., Cham :, Springer International Publishing ; Imprint Springer, 1 online resource (XIV, 466 p. 121 illus., 102 illus. in color.), 2017., isbn:3-319-70936-4, https://bibsys-ur.userservices.exlibrisgroup.com/view/uresolver/47BIBSYS_UBIS/openurl-UIS?ctx_enc=info:ofi/enc:UTF-8&ctx_id=10_1&ctx_tim=2021-10-06T21:09:36IST&ctx_ver=Z39.88-2004&url_ctx_fmt=info:ofi/fmt:kev:mtx:ctx&url_ver=Z39.88-2004&rfr_id=info:sid/primo.exlibrisgroup.com-BIBSYS_ILS&rft_dat=ie=47BIBSYS_UBB:51191443570002207,ie=47BIBSYS_UBA:5165449880002209,ie=47BIBSYS_UBTO:51110366750002205,ie=47BIBSYS_UBO:51207567690002204,ie=47BIBSYS_NTNU_UB:51224498680002203,ie=47BIBSYS_NMBU:5132718740002213,ie=47BIBSYS_HIB:5160332510002221,ie=47BIBSYS_HIOA:51113455050002212,ie=47BIBSYS_SIRUS:5136949190002256,ie=47BIBSYS_AHUS:5133512160002263,ie=47BIBSYS_NETWORK:71552229700002201,language=eng,view=UBIS&svc_dat=viewit&u.ignore_date_coverage=true&user_ip=10.16.56.140&req.skin=primoView online

E-book

Hands-on programming with R Garrett. Grolemund, Sebastopol, CA, O'Reilly Media, 2014, isbn:9781449359089, https://rstudio-education.github.io/hopr/ https://bibsys-ur.userservices.exlibrisgroup.com/view/uresolver/47BIBSYS_UBIS/openurl-UIS?ctx_enc=info:ofi/enc:UTF-8&ctx_id=10_1&ctx_tim=2021-10-06T21:30:37IST&ctx_ver=Z39.88-2004&url_ctx_fmt=info:ofi/fmt:kev:mtx:ctx&url_ver=Z39.88-2004&rfr_id=info:sid/primo.exlibrisgroup.com-BIBSYS_ILS&rft_dat=ie=47BIBSYS_UBO:51238999980002204,ie=47BIBSYS_HIT:5140965330002210,ie=47BIBSYS_NETWORK:71528430050002201,ie=47BIBSYS_HH:2148633000002214,language=eng,view=UBIS&svc_dat=viewit&u.ignore_date_coverage=true&user_ip=10.16.56.140&req.skin=primoView online

Book

Learning R Cotton, Richard, Sebastopol, CA :, O'Reilly, XIX, 377 sider :, 2013., isbn:9781449357108, http://duhi23.github.io/Analisis-de-datos/Cotton.pdf http://duhi23.github.io/Analisis-de-datos/Cotton.pdfView online

Kontakt

Study Program Director:

Tarjei Mandt Larsen

Course coordinator:

Yuko Onozaka

Course teacher:

Sufyan Ullah Khan

Tilbys av

UiS Business School

UiS School of Business and Law

The course description is retrieved from FS (Felles studentsystem). Version 1