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About this document
- Pages
- 9 pages
- Price
- $9 one-time, yours to keep
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- Format
- Subject
- Data Analysis, Statistics
- Module
- QNT275T · Week 2
These notes cover basic statistical concepts and data visualization techniques. They include definitions, examples, and questions on topics such as distributions, frequency polygons, dot plots, and various types of charts. This document is useful for students taking QNT275T in Week 2.
What's inside
- Symmetrical distribution and frequency polygons
- Dot plots and outliers
- Frequency distributions and stem-and-leaf displays
- Contingency tables and scatter plots
- Bar charts, pie charts, and Pareto charts
Who it is for: Students taking the QNT275T course, in Week 2. (Undergraduate)
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Summary
Data analysis and statistics are introduced. Students learn about different ways to display and understand data.
Types of data
Data can be qualitative or quantitative. Qualitative data is described using words. Quantitative data is described using numbers.
Graphical representations
Different graphs show different things. Bar charts, pie charts and Pareto charts show qualitative data. Histograms and scatter plots show quantitative data.
Measures of central tendency
The mean, median and mode are all measures of central tendency. They are different ways to find a typical value in a data set.
Measures of variation
The range, interquartile range and standard deviation are all measures of variation. They show how spread out the values in a data set are.
Key terms
- Dot plot
- A graph that shows each individual data point.
- Frequency distribution
- A table that shows how often each value occurs in a data set.
- Stem and leaf display
- A graph that shows the shape of a data set and keeps all the original data.
- Contingency table
- A table that shows how two categorical variables are related.
- Interquartile range
- The range of the middle 50% of a data set.
- Box and whiskers display
- A graph that shows the median, quartiles and possible outliers of a data set.
Questions this document helps with
- What is the difference between qualitative and quantitative data?
- Which graph should you use for qualitative data?
- How do you find the mean of a data set?
Summary written with AI from the document's text.
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