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IB Math Studies – Topic 6. Statistics. Daniela and Megan. IB Course Guide Description. IB Course Guide Description. IB Course Guide Description. Descriptive Statistics Different Types of Data: Categorical vs. Quantitative.
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IB Math Studies – Topic 6 Statistics Daniela and Megan
Descriptive StatisticsDifferent Types of Data: Categorical vs. Quantitative • Categorical – Describes a particular quality or characteristic. It can be divided into categories. • Example: The color of my shoes or different breeds of puppies Organizing categorical data: or or • Quantitative – Contains a numerical value. The information collected is termed numerical data. • Discrete – Takes exact number values and is often the result of counting. • i.e. number of TVs or number of houses on a street • Continuous – Takes numerical values within a certain range and is often a result of measuring. • i.e. the height of seniors or the weight of freshman Organizing Quantitative Data:
24 families were surveyed to find the number of people in the family. The results are:5, 9, 4, 4, 4, 5, 3, 4, 6, 8, 8, 5, 7, 6, 6, 8, 6, 9, 10, 7, 3, 5, 6, 6 Discrete • Is this data discrete or continuous? • Construct a frequency table for the data. • Display the data using a column graph. • Describe the shape of the distribution. Are there any outliers? • There are no outliers, all the numbers are generally close to one another. • What percentage of families have 5 or fewer people in them? 21%
Mean, Mode, Range, Median Mean, the average - Mode, most often – Range, subtract the smallest from the largest. Median, the middle number, When they’re lined up – From the greatest to the least. • Find the Mean, Mode, Range and Median • Mean: 5.17 • Mode: 5 • Range: 7 • Median: 5 • Q1 = 3+4 = 7/2 = 3.5 • Q3 = 6+7 = 13/2 = 6.5 • IQR (inner-quartile range) = Q3- Q1 6.5 – 3.5 = 3 IQR = 3
Practice • Median – 5.5 • Lower Quartile – 4 • Upper Quartile – 8 • Inner- Quartile Range – 4
Example: Pearson’s Correlation Coefficient 4 2.73 30 5.1 r = .98 Considering that it’s positive and very close to 1, it’s strong.
The x2 Test of Independence • Null Hypothesis – trying to prove that your variables are independent. • Degrees of Freedom – the number of rows on your table minus the number of columns on your table • There’s also expected frequency values