NURS 211 Prep Video 3 Notes

Video 3 Notes: Mean Median and Mode: Understanding and Calculating Measures of Central Tendency - Nurse Killam [YouTube] Normal distribution: -​ Simply put, it is the idea that when data are gathered from interval or ratio level measures and plotted on a graph, it will resemble a normal curve. -​ The three measures of central tendency described in this video would all fall at the same midline point on a normal distribution curve. -​ The appropriateness of each measure is also influenced by the level of measurement used in the study. Mean (M) = Average: -​ In statistics, mean is synonymous with the average. -​ To calculate the mean or average of a group of numbers, first add all the numbers. Then, divide by the number of values. Benefits: -​ Best measure for symmetrical distributions. -​ The mean is influenced by all data. -​ However, the larger the data set the smaller the influence of any extreme scores will be. -​ Most reliable. -​ The mean is the most commonly used measure because it is considered the most reliable measure of central tendency when making inferences from a sample population. -​ Only good for Interval and Ratio data. Limitations: -​ Best when there are no outliers or extremes. Median = Middle: -​ The Median is the value in the middle of a set of data. -​ To calculate the median you need to find out the point at which 50% of the values are higher and 50% of the values are lower. -​ To calculate it, first you need to arrange the numbers in order from lowest to highest. -​ Then, count to determine if there is an odd or even number of values. -​ If the number of values is odd: -​ Median = Middle value -​ If there is an odd number of values just pick the value in the middle of the range; the one with the same number of values above and below it. -​ If the number of values is even: -​ Median = Mean of the middle Values. If there is an even number of values simply divide the two numbers in the middle by 2. Benefits: -​ Good for asymmetrical data -​ Unlike the Mean, the Median is not influenced by extreme values in a data set. -​ Therefore, it is a good measure to use when distributions are not symmetrical. -​ If a researcher is working with data that are not normally distributed and wants to know what the typical score is the median is likely the best measure to use. -​ Works for Oridnal, Interval, and Ratio data. Limitations: -​ Does not account for extreme scores. -​ The median is limited because it is not algebraically defined. -​ Instead it is simply the point in the middle of the data set. -​ Not appropriate for Nominal data. Mode = Most Frequent: -​ The Mode is the most frequent value, number or category in a set of data. -​ The mode is calculated by examining the data to see which number appears most. -​ In a testing situation you would likely order the numbers then count the frequency of any number that appears multiple times to determine the mode. -​ Arrange the numbers in order in the table or graph. -​ Count the frequency of each number to see which number appears most. Benefits: -​ The Mode is the only appropriate measure of central tendency you can use for Nominal data. -​ Can also be used for Oridnal, Interval, and Ratio data. -​ While it can be used for all levels of measurement, it is considered unstable since fluctuations are likely between sample populations. Limitations: -​ Cannot be used if all the scores are different. -​ Sometimes there is no mode. -​ If all scores are different the mode does not exist. -​ There may be several Modes -​ If several values occur with equal frequency there are several modes. -​ Cannot be used for further calculations -​ It can only help to describe the central tendency of the population. -​ Unstable.