IB Math Studies – Topic 6 Daniela and Megan
IB Course Guide Description
Descriptive Statistics Different 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:
Different Types of Distribution
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 a)Is this data discrete or continuous? b)Construct a frequency table for the data. c)Display the data using a column graph. d)Describe the shape of the distribution. Are there any outliers? a)There are no outliers, all the numbers are generally close to one another. e)What percentage of families have 5 or fewer people in them? Discrete NumberFrequency %
Continuous Data
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 a.Median – 5.5 b.Lower Quartile – 4 c.Upper Quartile – 8 d.Inner- Quartile Range – 4
Box and Whisker Plots
2 Variable-Statistics: Correlation
Pearson’s Correlation Coefficient
Example: Pearson’s Correlation Coefficient Considering that it’s positive and very close to 1, it’s strong. r =.98
How to do Correlation Coefficient on the Calculator
Least Squares Regression
The x 2 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
The x 2 Test of Independence