Unit 3 Review. Data: – A variable is an attribute that can be measured – One Variable Data: measures only 1 attribute for each data point. – Two Variable.

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Presentation transcript:

Unit 3 Review

Data: – A variable is an attribute that can be measured – One Variable Data: measures only 1 attribute for each data point. – Two Variable Data: measures 2 attributes for each data point. One Variable DataTwo Variable Data -Tally Charts -Frequency Tables -Bar Graphs -Histograms -Circle Graphs -Pictographs -Ordered Pairs -Scatter Plots -Two –Column Tables of Values

Graphs: – Know how to draw a graph. – Always include a TITLE – Dependent Variable goes on the y-axis – Independent Variable goes on the x-axis – Label the dependent and independent variables – Label the x and y axes (with an x and a y!)

Correlation: – Is a relationship between 2 variables Positive Correlation: – Both variables increase together – Points on the graph go “up and to the right” Negative Correlation: – One variable increases while the other variable decreases. – Points on the graph go “down and to the right”

Correlation: Positive CorrelationNegative Correlation

Correlation: – A correlation DOES NOT indicate a Cause-and- Effect Relationship. It indicates that there MIGHT be a cause-and-effect relationship. – Weak Correlation – Points are spread out – Strong Correlation – Points are packed tightly together along a line. – No Correlation – Points are just all over the place. No real trend.

Line of Best Fit: – Also called: Regression Line Trend Line – Must fit the data trend and should have as many points on the line as possible. – If all points cannot be on the line then there should be as many points on the line as possible AND the same number of points above the line as there are below the line

Determine an equation for the line of best fit Use the equation to predict the average of a student who does 25 minutes of homework. Use the equation to predict the amount of homework done by a student who is earning 95%

Predictions: – Predictions can be made by using the Line of Best Fit. – Interpolation: Prediction of data points BETWEEN KNOWN points. – Extrapolation: Prediction of data points OUTSIDE KNOWN points.

Predictions: – When using a graph to Interpolate or Extrapolate make sure to: Draw in the dotted line from the given axis up (or over) to the line of best fit and then over (or down) to the other axis. (SHOW YOUR WORK!!) – Eg.

Reliability of a Linear Model: – What can reduce the reliability of a Linear Model? A WEAK linear correlation A non-linear correlation Data that are too clustered Outliers in the data A data sample that is too SMALL A data sample that is BIASED

These Notes are a STARTING POINT. You need to add things that YOU want in YOUR note. This is just how I would organize things and how my brain works. Yours might be different, so adjust the information so it fits what you need. You should be MEMORIZING the information in the notes (don’t necessarily memorize the examples unless you want to)

Once you can re-write your notes after you’ve taken a few hour break, without looking at the originals and from reading them, then Do as many practice questions as you can find. If you need more questions, see me and I’ll provide more. Use your textbook for info, examples, and practice questions.

Textbook: – Every section of the textbook has practice questions associated with it. – Every Chapter has a: Mid-Chapter Review Section halfway thru the chapter Chapter Summary at the end of the chapter. Chapter Review questions at the end of the chapter Chapter Practice Test – It’s an almost endless supply of questions…….Use them! – Re-do your old tests too to test yourself.