Scatter Plots Quiz
The question sheet
Reveal any answer as you study-
What is the most common and easiest way to display the relation between two variables x and y?
- A scatter plot
- A pie chart
- A histogram
- A box plot
Reveal answer
Answer: A scatter plot
Source evidence
PDF page 690: Before we take up the discussion of linear regression and correlation, we need to examine a way to display the relation between two variables x and y. The most common and easiest way is a scatter plot. The following example illustrates a scatter plot.
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According to the m-commerce example, what does x represent?
- The number of users
- The year
- The type of phone
- Millions of dollars
Reveal answer
Answer: The year
Source evidence
PDF page 691: In Europe and Asia, m-commerce is popular. M-commerce users have special mobile phones that work like electronic wallets as well as provide phone and Internet services. Users can do everything from paying for parking to buying a TV set or soda from a machine to banking to checking sports scores on the Internet. For the years 2000 through 2004, was there a relationship between the year and the number of m-commerce users? Construct a scatter plot. Let x = the year and let y = the number of m-commerce users, in millions.
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According to the data table, how many m-commerce users (in millions) were there in 2004?
- 0.5
- 33.0
- 47.0
- 20.0
Reveal answer
Answer: 47.0
Source evidence
PDF page 691: x (year) y (# of users) 2000 0.5 2002 20.0 2003 33.0 2004 47.0
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In the m-commerce example, the number of users is measured in what units?
- Millions
- Hundreds
- Thousands
- Billions
Reveal answer
Answer: Millions
Source evidence
PDF page 691: In Europe and Asia, m-commerce is popular. M-commerce users have special mobile phones that work like electronic wallets as well as provide phone and Internet services. Users can do everything from paying for parking to buying a TV set or soda from a machine to banking to checking sports scores on the Internet. For the years 2000 through 2004, was there a relationship between the year and the number of m-commerce users? Construct a scatter plot. Let x = the year and let y = the number of m-commerce users, in millions.
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Before creating a scatter plot on the calculator, what must be true of the other plots?
- They must be red
- They must be saved
- They must be OFF
- They must be ON
Reveal answer
Answer: They must be OFF
Source evidence
PDF page 691: (Make sure the other plots are OFF.)
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After graphing data, which key can you press to see the scaling of the axes?
- ZOOM
- WINDOW
- STAT
- GRAPH
Reveal answer
Answer: WINDOW
Source evidence
PDF page 691: the data. You can press WINDOW to see the scaling of the axes.
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In Amelia's example, the number of points she scores in a game goes up in response to what?
- Her height
- The season
- Hours practicing jump shot
- Number of games played
Reveal answer
Answer: Hours practicing jump shot
Source evidence
PDF page 691: the number of points she scores in a game goes up in response to the number of hours she practices her jump shot each week. She records the following data:
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In Amelia's data, how many points did she score when practicing 12 hours?
- 33
- 36
- 28
- 31
Reveal answer
Answer: 36
Source evidence
PDF page 692: X (hours practicing jump shot) Y (points scored in a game) 5 15 7 22 9 28 10 31 11 33 12 36
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In Amelia's data, how many points were scored when practicing 5 hours?
- 22
- 28
- 31
- 15
Reveal answer
Answer: 15
Source evidence
PDF page 692: X (hours practicing jump shot) Y (points scored in a game) 5 15 7 22 9 28 10 31 11 33 12 36
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A scatter plot shows what feature of a relationship between variables?
- The mode
- The median
- The direction
- The mean
Reveal answer
Answer: The direction
Source evidence
PDF page 692: A scatter plot shows the direction of a relationship between the variables. A clear direction happens when there is either:
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For a scatter plot with a linear pattern, when is the relationship considered strong?
- When there are few points
- When points form a circle
- When points are close to a straight line
- When points are scattered widely
Reveal answer
Answer: When points are close to a straight line
Source evidence
PDF page 693: In this chapter, we are interested in scatter plots that show a linear pattern. Linear patterns are quite common. The linear relationship is strong if the points are close to a straight line, except in the case of a horizontal line where there is no relationship. If we think that the points show a linear relationship, we would like to draw a line on the scatter plot. This line can be calculated through a process called linear regression. However, we only calculate a regression line if one of the variables helps to explain or predict the other variable. If x is the independent variable and y the dependent variable, then we can use a regression line to predict y for a given value of x
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When all points fall on a horizontal line, the relationship shown is:
- Exponential
- No relationship
- Curved
- Very strong
Reveal answer
Answer: No relationship
Source evidence
PDF page 692: You can determine the strength of the relationship by looking at the scatter plot and seeing how close the points are to a line, a power function, an exponential function, or to some other type of function. For a linear relationship there is an exception. Consider a scatter plot where all the points fall on a horizontal line providing a "perfect fit." The horizontal line would in fact show no relationship. When you look at a scatterplot, you want to notice the overall pattern and any deviations from the pattern. The following scatterplot examples illustrate these concepts.
PDF page 693: In this chapter, we are interested in scatter plots that show a linear pattern. Linear patterns are quite common. The linear relationship is strong if the points are close to a straight line, except in the case of a horizontal line where there is no relationship. If we think that the points show a linear relationship, we would like to draw a line on the scatter plot. This line can be calculated through a process called linear regression. However, we only calculate a regression line if one of the variables helps to explain or predict the other variable. If x is the independent variable and y the dependent variable, then we can use a regression line to predict y for a given value of x
Introductory Statistics
Introductory Statistics by OpenStax, used under CC BY 4.0. Changes made by Stratacademy.
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