Let’s Better Understand About Correlation – Data Analysis

a1. Correlation

Technical definition of outliers can be seen as – an observation point that is distant from other observations. In other words, outliers refer to the values which are found to disperse from the central tendency of the data.

To put it simply, outliers are values far from the mean/median of data, disperse multiple times of standard deviation. The presence of outliers in the dataset indicate two situations: variability of data and measurements errors. There are many ways to determine the presence of outliers and most general applied techniques are: z-score and IQR (interquartile range). Data Analysis

a2.  Z-score

Z-Score: is a score which measures the number of standard deviations from mean of the population. The accepted value z-score is 3 and – 3. Therefore, value from higher than mean plus 3 times of standard deviations either positive or negative is considered outliers as shown in the graph below.

Z-Score: is a score which measures the number of standard deviations from mean of the population. The accepted value z-score is 3 and – 3. Therefore, value from higher than mean plus 3 times of standard deviations either positive or negative is considered outliers as shown in the graph below.

Z-Score: is a score which measures the number of standard deviations from mean of the population. The accepted value z-score is 3 and – 3. Therefore, value from higher than mean plus 3 times of standard deviations either positive or negative is considered outliers as shown in the graph below.

Z-Score: is a score which measures the number of standard deviations from mean of the population. The accepted value z-score is 3 and – 3. Therefore, value from higher than mean plus 3 times of standard deviations either positive or negative is considered outliers as shown in the graph below.

Z-Score: is a score which measures the number of standard deviations from mean of the population. The accepted value z-score is 3 and – 3. Therefore, value from higher than mean plus 3 times of standard deviations either positive or negative is considered outliers as shown in the graph below.

Z-Score: is a score which measures the number of standard deviations from mean of the population. The accepted value z-score is 3 and – 3. Therefore, value from higher than mean plus 3 times of standard deviations either positive or negative is considered outliers as shown in the graph below.

Technical definition of outliers can be seen as – an observation point that is distant from other observations. In other words, outliers refer to the values which are found to disperse from the central tendency of the data.

To put it simply, outliers are values far from the mean/median of data, disperse multiple times of standard deviation. The presence of outliers in the dataset indicate two situations: variability of data and measurements errors. There are many ways to determine the presence of outliers and most general applied techniques are: z-score and IQR (interquartile range). Data Analysis

Technical definition of outliers can be seen as – an observation point that is distant from other observations. In other words, outliers refer to the values which are found to disperse from the central tendency of the data.

To put it simply, outliers are values far from the mean/median of data, disperse multiple times of standard deviation. The presence of outliers in the dataset indicate two situations: variability of data and measurements errors. There are many ways to determine the presence of outliers and most general applied techniques are: z-score and IQR (interquartile range). Data Analysis

Technical definition of outliers can be seen as – an observation point that is distant from other observations. In other words, outliers refer to the values which are found to disperse from the central tendency of the data.

To put it simply, outliers are values far from the mean/median of data, disperse multiple times of standard deviation. The presence of outliers in the dataset indicate two situations: variability of data and measurements errors. There are many ways to determine the presence of outliers and most general applied techniques are: z-score and IQR (interquartile range). Data Analysis

Technical definition of outliers can be seen as – an observation point that is distant from other observations. In other words, outliers refer to the values which are found to disperse from the central tendency of the data.

To put it simply, outliers are values far from the mean/median of data, disperse multiple times of standard deviation. The presence of outliers in the dataset indicate two situations: variability of data and measurements errors. There are many ways to determine the presence of outliers and most general applied techniques are: z-score and IQR (interquartile range). Data Analysis

Technical definition of outliers can be seen as – an observation point that is distant from other observations. In other words, outliers refer to the values which are found to disperse from the central tendency of the data.

To put it simply, outliers are values far from the mean/median of data, disperse multiple times of standard deviation. The presence of outliers in the dataset indicate two situations: variability of data and measurements errors. There are many ways to determine the presence of outliers and most general applied techniques are: z-score and IQR (interquartile range). Data Analysis

Technical definition of outliers can be seen as – an observation point that is distant from other observations. In other words, outliers refer to the values which are found to disperse from the central tendency of the data.

To put it simply, outliers are values far from the mean/median of data, disperse multiple times of standard deviation. The presence of outliers in the dataset indicate two situations: variability of data and measurements errors. There are many ways to determine the presence of outliers and most general applied techniques are: z-score and IQR (interquartile range). Data Analysis

Technical definition of outliers can be seen as – an observation point that is distant from other observations. In other words, outliers refer to the values which are found to disperse from the central tendency of the data.

To put it simply, outliers are values far from the mean/median of data, disperse multiple times of standard deviation. The presence of outliers in the dataset indicate two situations: variability of data and measurements errors. There are many ways to determine the presence of outliers and most general applied techniques are: z-score and IQR (interquartile range). Data Analysis