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Date: REVIEW: Scatter Plots Vocabulary to Know: hypothesis primary data secondary data population sample random sample bias outliers trend relationship correlation interpolate extrapolateSetting Up
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To fill out review scatter plots, follow these steps:
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Identify the variables you want to compare in the scatter plot.
03
Collect the data points for each variable.
04
Plot the data points on the scatter plot, with one variable represented on the x-axis and the other variable on the y-axis.
05
Use different markers or colors to differentiate different groups or categories, if applicable.
06
Interpret the scatter plot by analyzing the patterns, trends, or correlations between the variables.
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Add labels, titles, and a legend to make the scatter plot more informative and understandable.
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Review and analyze the scatter plot to draw conclusions or insights about the relationship between the variables.

Who needs review scatter plots?

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Review scatter plots are useful for anyone who wants to visually analyze the relationship between two variables.
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Specifically, the following individuals or groups may benefit from using review scatter plots:
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- Researchers and scientists conducting experiments or studies
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- Data analysts and statisticians analyzing data
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- Business professionals analyzing sales data or market trends
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- Students learning about correlation and association between variables
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- Any individual or organization interested in data visualization and exploration
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Review scatter plots are visual representations of data points in a two-dimensional space showing the relationship between variables.
Individuals or organizations conducting data analysis or research projects may be required to file review scatter plots.
To fill out review scatter plots, data points need to be plotted on a graph with one variable on the x-axis and the other variable on the y-axis.
The purpose of review scatter plots is to identify patterns, trends, and relationships between variables in a dataset.
Review scatter plots should include data points, labels for variables, and a title describing the analysis.
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