Normal Probability Plot

What is a normal probability plot?

• A normal probability plot is used to assess whether a set of data follows a uniform distribution.

• A normal probability plot is a graphical tool used to assess whether a set of data follows a normal distribution.

• A normal probability plot is a graphical tool used to assess whether a set of data follows a linear regression model.

• A normal probability plot is a graphical tool used to assess whether a set of data follows a exponential distribution.

How would you interpret a normal probability plot?

• A normal probability plot is used to assess if a dataset follows a bimodal distribution.

• A normal probability plot is used to assess if a dataset follows a skewed distribution.

• A normal probability plot is used to assess if a dataset follows a normal distribution or comes from a population that is normal.

• A normal probability plot is used to assess if a dataset follows a uniform distribution with no outliers.

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What does a straight line on a normal probability plot indicate?

• The data does not follow a normal distribution.

• The data is skewed.

• The data is random.

• The data follows a normal distribution.

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What does a curved line on a normal probability plot indicate?

• The data does not follow a normal distribution.

• The data follows a normal distribution.

• The data is perfectly normally distributed.

• The data is skewed to the left.

How can you determine if a dataset follows a normal distribution using a normal probability plot?

• Plot the data with the expected quantiles of a normal distribution, and check if the points roughly follow a straight line.

• Calculate the mean and standard deviation of the dataset and compare them to the expected values for a normal distribution.

• Plot the data with the expected quantiles of a normal distribution, and check if the points roughly follow a curve pattern.

• Count the number of data points that fall within certain intervals and compare them to the expected proportions for a normal distribution.

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What is the main reason to create a normal probability plot (QQ plot)?

• Determine if the mean or median should be used for measure of center for a data set

• To assess if a sample comes from a population that is normal distributed

• Identify outliers for a heavy skewed distribution

• Assess if the correlation between two variables is high

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What are some common types of graphs used to represent a normal probability plot?

• Line graph

• Q-Q plot, P-P plot

• Bar graph

• Pie chart

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How can you create a Quantile–Quantile QQ plot (normal probability plot) in StatCrunch?

• Once the data is in StatCrunch, click on "Graph" and then select "QQ Plot"

• Once the data is in StatCrunch, click on "Stat" and then select "Summary Stats"

• Once the data is in StatCrunch, click on "Graph" and then select "Histogram"

• Once the data is in StatCrunch, click on "Stat" and then select "Table" and "Frequency"

The graph at the left is a QQ plot. What can you conclude from this graph?

• The QQ plot shows that the sample is likely NOT from a normal population.

• The QQ plot shows that the sample is likely from a normal population.

• The QQ plot is inconclusive.

• The curve pattern proves that the sample is normally distributive.

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The graph at the left is a QQ plot. What can you conclude from this graph?

• The QQ plot shows that the sample is likely NOT from a normal population.

• The QQ plot shows that the sample is likely from a normal population.

• The QQ plot is inconclusive.

• The linear proves that the sample is skewed.

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