Scatterplots Lauren Goldenberg Stephen Goldsman Cassandra Raginsky.

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Scatterplots Lauren Goldenberg Stephen Goldsman Cassandra Raginsky

Correlations Positive Correlation: In a positive correlation, as the values of one of the variables increase, the values of the second variable also increase. Likewise, as the value of one of the variables decreases, the value of the other variable also decreases. Negative Correlation: In a negative correlation, as the values of one of the variables increase, the values of the second variable decrease. Likewise, as the value of one of the variables decreases, the value of the other variable increases. No Correlation: where a change in one set of data has no effect on the other set

Linear Regression Linear Regression is the relation between variables when the regression equation is linear: y = mx + b This is like the height and shoe size example we did in class

Quadratic Regression Quadratic Regression is a process by which the equation of a parabola of "best fit" is found from a set of data. This is like the chicken wire example from class.

Exponential Regression Exponential Regression can be used to find an equation that best fits the relationship between a group of random variables. It assists in drawing conclusion about a set of data.

Exponential Regression M&M EXPERIMENT

Directions 1)Pour all M&M’s onto the paper towel 2)Count how many of the 30 have the letter M face up 3)Subtract that number from the start, and write the total in an (x,y) ordered pair. For example, trial 1 may leave you with 17 M&M’s left. (1,17) 4)Eat the ones with an M, repeat until all are gone 5)Graph your results on the graph paper

Homework There was a survey done on 14 girl’s height and weight. What is the ling of best fit? And does it have a positive Correlation or a Negative Correlation or no Correlation? Make your window in the calculator be x-min:0 x-max:80 y-min:0 y-max: 200 HeightWeight

Works Cited "WordNet Search " WordNet Search N.p., n.d. Web. 10 Mar "Quadratic Regression." Quadratic Regression. N.p., n.d. Web. 10 Mar