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MATH 1060 - Statistics for Data Analysis

Mathematics Part-time Studies Course

School of Computing and Academic Studies

BCIT is planning for a substantial return to on-campus activity for the fall 2021 term as informed by BC Public Health Officer guidelines. Refer to each course listing for details.

Course Details

This hands-on course introduces descriptive statistics, basic inferential statistics, linear regression, and probability concepts and calculations. Emphasis throughout the course will be placed on using statistical methods for the exploration and analysis of data sets. This introduction will enable students to use statistics for data analysis, will prepare them for “Data Analytics/Mining,” and covers topics appropriate for anyone seeking a first statistics course. Labs and exercises employ standard graphical methods to represent statistical data. Hypothesis tests, including ANOVA, are used to test for significant differences between multiple groups. Students will be introduced to the open source R Programming language, a statistical analysis tool used to extract meaningful information from a variety of scientific, industrial and commercial data sets. Upon successful completion, students will be able to carry out calculations, perform statistical decision making and solve problems with involving collected data. This course prepares the student to move on to MATH 3060 and is a required course for the Applied Data Analytics Certificate offered by BCIT Computing.

Prerequisite(s)

Math 12 Pre-Calculus or equivalent

Credits

3.0

Cost

$673.25

Winter 2022

Below are two offerings of this course for the Winter 2022 term.

CRN 84201

Thu Jan 06 - Thu Mar 31 13 Weeks

Class Meeting Times

Dates Days Times Locations
Jan 06 - Mar 31 Thu 18:30 - 21:30 BBY SE12 Rm. 324

Instructor

Vahid Dabbaghian

Course Outline

TBD – see Learning Outcomes in the interim

Cost

$673.25

Notes

  1. THIS COURSE WILL BE DELIVERED IN-PERSON. Refreshing your math skills prior to starting MATH 1060 is strongly recommended and we suggest taking MATH 0060. **FINAL EXAM on Thursday, March 31st**

3 seats remaining as of Dec 5, 2021 3:52 am (PST). Availability may change at any time.

CRN 85573

Sat Jan 08 - Thu Mar 31 13 Weeks

Class Meeting Times

Dates Days Times Locations
Jan 08 - Mar 31 Sat 09:30 - 12:30 BBY

Instructor

Takashi Nakamura

Course Outline

TBD – see Learning Outcomes in the interim

Cost

$673.25

Notes

  1. ***IMPORTANT INFORMATION READ CAREFULLY*** COURSE FORMAT IS SYNCHRONOUS ONLINE LECTURES AND HAS TWO MANDATORY EXAM SESSIONS: 1. Midterm: Saturday, 26 February 2022 at 9:30 am in Room SE06-107 on the Burnaby Campus. 2. Final: Thursday, 31 March, 2022 at 6:30 pm in Room SE06-107 in the Burnaby Campus. Refreshing your math skills prior to starting MATH 1060 is strongly recommended and we suggest taking MATH 0060.
  2. Important course information will be sent to you prior to your course start date. Check your myBCIT email account to access this information.

This course offering is full. Please check this page for other currently available offerings, subscribe to receive email updates or contact us with your comments or questions.

Full

Learning Outcomes

Upon successful completion of this course, the student will be able to:

  • Compute and understand the meaning of mean, median, range, standard deviation, variance, percentiles and standard scores.
  • Use and understand standard graphical methods of representing statistical data.
  • Use R to process and analyse data.
  • Perform basic probability calculations.
  • Solve problems with statistical variables that have a binomial, Poisson, normal or other probability distributions.
  • Describe the basic procedures for null hypothesis testing; define, explain, illustrate basic concepts such as null and alternate hypotheses, type 1 and 2 errors, level of significance, critical values, test statistic, rejection region, one-tailed and two-tailed tests; power; determination of sample size.
  • Carry out calculations and statistical tests related to sample means, sample proportions, chi-square distribution, and correlation and regression.
  • Use ANOVA to test hypotheses on differences between multiple groups.
  • Estimate with confidence intervals for population parameters (means, difference between means, difference between proportions).
  • Apply principles of linear correlations and regression and determine correlation coefficients between different data variables.
  • Use multiple regression to predict a response variable and determine the most significant predictor variables.

Effective as of Spring/Summer 2016

Related Programs

MATH 1060 is offered as a part of the following programs:

School of Computing and Academic Studies

  1. Applied Data Analytics
    Part-time   Certificate
  2. Computer Systems
    Part-time   Diploma

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