#### Didn’t find what you are looking for? Scatterplots ### A nutritionist collects the weight of college students in the first semester, then again in the second semester. What is the best way to visually present this data? a) Line Graphs b) Scatterplots c) Bar Graphs d) Pie Charts

Scatterplots ### Make a scatterplot for the data. Height and Weight of Females Height (in.): 58, 60, 62, 64, 65, 66, 68, 70, 72 Weight (lb): 115, 120, 125, 133, 136, 115, 146, 153, 159

Scatterplots ### Match the values of r with the accompanying scatterplots 0.723,-0.353,0.353,0.998 and -0.998 scatterplots 1,2,3,4,5 Scatterplots ### Sketch a scatterplot where the association is linear, but the correlation is close to [r = 0].

Scatterplots ### Unusual points Each of the four scatterplots that follow shows a cluster of points and one “stray” point. For each, answer these questions: 1) In what way is the point unusual? Does it have high leverage, a large residual, or both? 2) Do you think that point is an influential point? 3) If that point were removed, would the correlation be- come stronger or weaker? Explain. 4) If that point were removed, would the slope of the re- gression line increase or decrease? Explain Scatterplots ### Give relations mentioned in the given scatterplots A & B Scatterplots ### a. Make a scatterplot for the data in the table below. Height and Weight of Football Players Height (in.): 77 75 76 70 70 73 74 74 73 Weight (lb): 230 220 212 190 201 245 218 260 196 b. Which display - the table or the scatter plot - do you think is a more appropriate display of the data? Explain your reasoning.

Scatterplots ### Use a scatterplot and the linear correlation coefficient r to determinewhether there is a correlation between the two variables. [x 1 2 2 5 6 y 2 5 4 15 15]

Scatterplots ### How to prove that a normally distributed assumption was fulfilled for the Two-Proportional z-test? Select all relevant assumptions. Residual graphs do not have a pattern Scattered plots are linear Scattered plots do not have a pattern Normal sample distribution: npge5&n(1-p)ge5 Bell-shaped histograms Histograms are uniform Residual graphs are linear Residual graphs are linear box plots have less than two outliers Normal quantile plots do not have a pattern Normal sample distribution: n,p,ge5,n,(1-p)ge5,n_2p_2ge5&91-p_2)ge5 Normal sample distribution: n'sge30 or populations usually are distributed

Scatterplots ### Make a scatterplot for each set of data. Tell whether the data show a linear association or a nonlinear association. (1,2),(7,9.5),(4,7),(2,4.2),(6,8.25),(3,5.8),(5,8),(8,10),(0,0)

Scatterplots ### Below is a dot plot of the number of snapchats sent per day in Mr. Elkins' class. Part A: Which value is smaller, the mean or the median?

Scatterplots ### Make a scatterplot of the data. Use the year on the horizontal scale and the number of ounces on the vertical scale. Available Drink Sizes at a Convenience Store Year, Sizes Available (cm) 1973: 12, 20 1976: 12, 16, 20 1978: 12, 16, 20, 32 1983: 12, 16, 20, 32, 44 1988: 12, 16, 20, 32, 44, 64 2003: 12, 20, 32, 44, 64 2005: 20, 32, 44, 64

Scatterplots ### Suppose x1 and x2 are predictor variables for a response variable y. a. The distribution of all possible values of the response variable corresponding to particular values of the two predictor variables is called a distribution of the response variable. b. State the four assumptions for multiple linear regression inferences

Scatterplots ### How can two variables be displayed in a scattergram?

Scatterplots ### Make a scatterplot for the data. Length (mi) and Water Flow $$\displaystyle{\left({1},{000}{f}\frac{{t}^{{{3}}}}{{s}}\right)}$$ of Rivers Length: 2540, 1980, 1460, 1420, 1290, 1040, 886, 774, 724, 659 Flow: 76, 225, 41, 58, 56, 57, 68, 67, 67, 41

Scatterplots ### Describe about the three positive relationships of Scatterplots?

Scatterplots ### Make a scatterplot for the data in each table. Use the scatter plot to identify and clustering or outliers in the data. Value of Home Over Time Number of Years Owned: 0, 3, 6, 9, 12, 15, 18, 21 Value (1,000s of \$): 80, 84, 86, 88, 89, 117, 119, 86

Scatterplots ### Predicting Land Value Both figures concern the assessed value of land (with homes on the land), and both use the same data set. (a). Which do you think has a stronger relationship with value of the land-the number of acres of land or the number of rooms n the homes? Why? b. Il you were trying to predict the value of a parcel of land in e arca (on which there is a home), would you be able to te a better prediction by knowing the acreage or the num- ber of rooms in the house? Explain. (Source: Minitab File, Student 12. "Assess.") Scatterplots ### The following data on = soil depth (in centimeters) and y = percentage of montmorillonite in the soil were taken from a scatterplot in the paper "Ancient Maya Drained Field Agriculture: Its Possible Application Today in the New River Floodplain, Belize, C.A." (Agricultural Ecosystems and Environment : 67-84): a. Draw a scatterplot of y versus x. b. The equation of the least-squares line is 0.45x. Draw this line on your scatterplot. Do there appear to be any large residuals? c. Compute the residuals, and construct a residual plot. Are there any unusual features in the plot? x 40 50 60 70 80 90 100 y 58 34 32 30 28 27 22 $$\displaystyle{\left[\hat{{{y}}}={64.50}\right]}$$. 