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IMPORTANT NOTE:There have been changes to this course for 2021. For 2020 enrolments please check the individual offering description below to confirm details for:
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.
|2020 *||Semester One full semester||Internal||Manawatu Campus|
|2020 *||Semester One full semester||Distance|
|2020 *||Semester Two full semester||Internal||Manawatu Campus|
|2020 *||Semester Two full semester||Internal||Auckland Campus|
|2020 *||Semester Two full semester||Distance|
|2020 *||Summer School||Distance|
|2021||Semester One full semester||Distance|
|2021||Semester One full semester||Internal||Manawatu Campus|
|2021||Semester Two full semester||Internal||Auckland Campus|
|2021||Semester Two full semester||Distance|
|2021||Semester Two full semester||Internal||Manawatu Campus|
* Due to recent changes you should carefully check this offering to confirm details before you enrol.
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