Chapter 1 Review MDM 4U Mr. Lieff. 1.1 Displaying Data Visually Types of data Quantitative Discrete – only whole numbers are possible Continuous – decimals/fractions.

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Presentation transcript:

Chapter 1 Review MDM 4U Mr. Lieff

1.1 Displaying Data Visually Types of data Quantitative Discrete – only whole numbers are possible Continuous – decimals/fractions are possible Qualitative / Categorical – non-numeric Population – the group being studied Census – data is collected from every member Sample – data is collected from a subset of the pop’n

1.1 Displaying Data Visually Frequency Table, Stem and Leaf Plot Measures of Central Tendency (mean/median/mode) Read information from the following graphs; when to use them One variable Bar Graphs (qualitative or discrete data) Histograms (data in intervals or continuous data) Broken Line Graphs (trends in one variable over time) Pie Graphs (comparing quantities to a whole) Two variable Scatter Plots (compare two numeric variables) Stacked Bar Graphs (individual freq. of two non-numeric vars) Double-Bar Graphs (total freq. of two non-numeric vars)

1.2 One Variable Data When can we draw conclusions? Must see a trend Must have a sufficiently large sample Correlations vs. Causal Relationships

1.3 Visualizing Trends Variables Independent (x-axis) Dependent (y-axis) Syntax: dependent vs. independent e.g., graph of weight vs. height Scatter Plots and Correlations Trends – positive/negative (or none); weak/strong Lines of Best Fit Median-Median – based on 3 median points Least Squares Line – based on residuals (every point)

1.4 Trends in Technology Regression (linear or non-linear) Correlation Coefficient r (-1 to 1) Describes strength and direction of correlation Coefficient of Determination r 2 (0 to 1) Gives the % of the change in y that is due to x Residuals Vertical distances between point and line of best fit The Least Squares line minimizes the sum of the squares of the residuals

1.5 – Misuse of Data 3D graphs are distorted Changing the scale Distorts differences / changes Small sample May allow you to draw invalid conclusions

Review pp # 1, 3-10 * you will not have to create a scatter plot on the test * see next 2 slides for graphs for #3 & 6

p. 72 #3

p. 72 #6