161.111 Applied Statistics (15 credits)

Statistical literacy, the ability to understand and reason with statistics and data, is becoming increasingly important as our world becomes more and more data-rich. This course focuses on developing statistical literacy in real-world contexts. We teach students to use software (Excel and RStudio) to summarise, display and analyse data. We explore data collection techniques including sampling methods and experimental design. We introduce statistical inference methods (confidence intervals, hypothesis testing and regression) with an emphasis on communicating results in context.

Note(s): 161.111 is a good fit for students without a strong background in computing or mathematics. From 161.111, students can continue onto 200-level statistics courses, but must complete 161.220 Data Analysis or 233.214 GIS and Spatial Statistics first. Students with a stronger computing or mathematical background should consider 161.122 Statistics which takes an in-depth approach to statistics with a strong focus on computing and allows entry into all 200-level statistics courses.

Requirements

• Restriction(s): 115.101, 161.101, 161.120, 161.122, 161.130, 161.140

Expected prior learning

• • At least 16 credits in NCEA Level 2 Mathematics from these standards: 91256, 91257, 91258, 91259, 91260, 91261, 91262, 91269; or passed any of these Massey University courses or equivalent: 124103 or any 100-level mathematics course (prefix 160).
    
    If you do not have this prior learning or equivalent you should enrol in one of these Massey University courses instead: • 160104 Introductory Mathematics for Science or • 124103 Biophysical Principles
    
    If it’s some time since you studied Mathematics at school, you can find out if you have the expected background by taking this maths quiz.

Offerings

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