Press "Enter" to skip to content

What does a scatter plot indicate?

A scatter plot (aka scatter chart, scatter graph) uses dots to represent values for two different numeric variables. The position of each dot on the horizontal and vertical axis indicates values for an individual data point. Scatter plots are used to observe relationships between variables.

When the data points in a scatter plot are randomly scattered the correlation between the two variables is weak?

If the data points are randomly scattered, then there is no relationship between the two variables; this means there is a low or zero correlation between the variables (Figure 2). Very low or zero correlation may result from a non-linear relationship between two variables.

What does each point on a scatter plot represent?

A scatterplot consists of an X axis (the horizontal axis), a Y axis (the vertical axis), and a series of dots. Each dot on the scatterplot represents one observation from a data set. The position of the dot on the scatterplot represents its X and Y values. And here is the same data displayed in a scatterplot.

How do you interpret a scatter diagram?

You interpret a scatterplot by looking for trends in the data as you go from left to right: If the data show an uphill pattern as you move from left to right, this indicates a positive relationship between X and Y. As the X-values increase (move right), the Y-values tend to increase (move up).

What is a scatter plot Quizizz?

The scatter plot shows the relationship between the number of chapters and the total number of pages for several books. Use the trend line to predict how many chapters would be in a book with 180 pages. 12 chapters. 15 chapters.

How do you deal with outliers in data?

5 ways to deal with outliers in data

  1. Set up a filter in your testing tool. Even though this has a little cost, filtering out outliers is worth it.
  2. Remove or change outliers during post-test analysis.
  3. Change the value of outliers.
  4. Consider the underlying distribution.
  5. Consider the value of mild outliers.

What does it mean when there are no outliers?

There are no outliers. Explanation: An observation is an outlier if it falls more than above the upper quartile or more than below the lower quartile. The minimum value is so there are no outliers in the low end of the distribution.

How does an outlier affect the mean and standard deviation?

A single outlier can raise the standard deviation and in turn, distort the picture of spread. For data with approximately the same mean, the greater the spread, the greater the standard deviation. If all values of a data set are the same, the standard deviation is zero (because each value is equal to the mean).

How does an extreme value affect the mean?

One extreme value is still only one value, so it cannot affect the mean very much. An extreme value cannot affect the mean if it is close to the mean. Since all values are summed, any extreme value can influence the mean to a large extent.

What is an outlier and how does it affect the confidence interval?

What is an outlier and how does it affect the confidence interval? a. An outlier stretches the interval because it increases the standard deviation. An outlier compacts the interval because it decreases the standard deviation.

Do outliers increase confidence interval?

The confidence intervals are affected by the presence of outliers. The outliers affect the mean and standard deviation. The values of mean and standard deviation are overvalued when extreme values are present.

What happens to confidence interval when we introduce outliers?

Confidence interval will increase with the introduction of outliers. We know that confidence interval depends on the standard deviation of the data. If we introduce outliers into the data, the standard deviation increases, and hence the confidence interval also increases.

What do outliers do to the width of a confidence interval?

I know that the size of a sample is inversely proportional to the width of a confidence interval, and that outliers tend to increase the width of the interval as well.

What does not affect the width of confidence interval?

In general, the narrower the confidence interval, the more information we have about the value of the population parameter. That is, the sample mean plays no role in the width of the interval. As the sample standard deviation s decreases, the width of the interval decreases.

What will decrease the width of a confidence interval?

The width of a confidence interval will be smaller when you have a larger sample size (because larger samples make sample statistics more reliable).

Which of the following affects the width of a confidence interval?

There are three factors that determine the size of the confidence interval for a given confidence level. These are: sample size, percentage and population size. The larger your sample, the more sure you can be that their answers truly reflect the population.