The frequency and variability of the two variables are measured together to see if they vary together. The bivariate analysis identifies any available relationship between two different variables. This allows the examination of each variable in the data set using different measures of frequency, variation, and central tendency. The univariate analysis considers only one variable at a particular time. These methods can be used for univariate analysis, bivariate analysis, or multivariate analysis as needed. A squared standard deviation gives the variance. Variance measures the degree of spread in the data set and is the average of squared deviations from the mean. Find the square root of the number obtained.Divide the sum of the squared deviation by N-1 (where N is the total number of values).Find the sum of the squared deviations.Get the squared values of each deviation.Subtract the mean from individual values to measure the deviation from the mean.

Standard deviation is calculated using six steps: A large value of the standard deviation indicates high variability. Standard deviation measures the average variability of the values in the data set or how far individual values are from the mean. The range indicates how far apart the values are. It can be calculated by subtracting the lowest value from the highest value. The range is the difference between the highest value of the data set and the lowest value. Any data set can have no mode, one mode, or multiple modes. Arranging the values in order from lowest to highest helps identify the mode. The mode is the value that appears most frequently in the set. If there are two values at the center, their mean is calculated to find the median. The median of the set is the value that is at the exact center of the set. Mean = Sum of values/Number of values B) Median Mean is the average of all the values and can be calculated by adding up all the values and dividing the total sum by the number of values. The various descriptive statistics methods used to arrive at the characteristics of the data set include: A) Mean Percentiles and quartile ranks indicate the measures of position. This method of calculation relies on a standardized value. This measures how individual values are positioned with one another. Measures of variation are calculated using the range, standard deviation, and variance. It helps identify the gap between the highest and lowest values and how far apart individual values are from the mean or the average. This shows how spread out the responses in the data set are. They identify certain points by computing the mean, median, and mode. Measures of central tendency indicate the average or the most common variable in the data set. It can be measured in numbers or percentages and shows how frequently a response or variable occurs. This measures how often a particular variable occurs in the distribution. There are four major types of descriptive statistics used to measure a given set of data characteristics. Hence, descriptive statistics form the first step and the basis of quantitative data analysis. It is paired with graphs and tables descriptive statistics offer a clear summary of the data’s complete collection.ĭescriptive statistics indicate that interpretation is the primary purpose, while inferential statistics make future predictions for a larger set of data based on descriptive values obtained. It converts large volumes of data and presents it in a simpler, more meaningful format that is easier to understand and interpret. It assigns numerical values to describe the trend of the samples collected. Important Tools in Descriptive Statisticsĭescriptive statistics describes or summarizes the basic features or characteristics of the data.Descriptive statistics and inferential statistics are the two methods used for this purpose. Quantitative data analysis of a large collection of data is made possible using certain numerical computations that give an understanding of the nature of the data collected and make it easier to interpret their trend.

Basic descriptive analysis