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  1. The Outliers Worksheet with Answer Key is a document that provides practice exercises and their solutions related to the concept of outliers in data analysis. These worksheets help students understand how to identify and analyze outlier values in a data set.

  2. 30 Νοε 2021 · It’s important to carefully identify potential outliers in your dataset and deal with them in an appropriate manner for accurate results. There are four ways to identify outliers: Sorting method. Data visualization method. Statistical tests (z scores) Interquartile range method.

  3. 4 Οκτ 2022 · Your outliers are any values greater than your upper fence or less than your lower fence. Example: Using the interquartile range to find outliers. We’ll walk you through the popular IQR method for identifying outliers using a step-by-step example. Your dataset has 11 values.

  4. An outlier is defined as being any point of data that lies over 1.5 IQRs below the first quartile (Q 1) or above the third quartile (Q 3)in a data set. High = (Q 3) + 1.5 IQR Low = (Q 1) – 1.5 IQR. Example Question: Find the outliers for the following data set: 3, 10, 14, 22, 19, 29, 70, 49, 36, 32.

  5. 2 Απρ 2023 · Are there any outliers in the data? What is the slope of the least-squares (best-fit) line? Interpret the slope. Answer. Size is \(x\), the independent variable, price is \(y\), the dependent variable. Check student’s solution. The relationship does not appear to be linear. \(\hat{y} = -745.252 + 54.75569x\) \(r = 0.8944\), yes it is significant

  6. 2 Απρ 2023 · In some data sets, there are values (observed data points) called outliers. Outliers are observed data points that are far from the least squares line. They have large "errors", where the "error" or residual is the vertical distance from the line to the point. Outliers need to be examined closely.

  7. Example. Let us find the outliers for the below data. 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, and 22.