Data and Statistics (For Business and Economics)

Explore how frequency distribution clarifies data by counting frequencies and building a distribution table for qualitative data. Analyze a shoe-brand survey of 50 responses to reveal Nike leading in popularity.

Compute relative frequency and percent frequency distributions by dividing class counts by the total and multiplying by 100. The example shows Nike at 30% and other classes.

Learn to construct a frequency distribution for qualitative data in Excel by using countif to count occurrences (for example Nike), lock ranges with absolute references, and fill the table efficiently.

Explore presenting data with vertical and horizontal bar graphs, plotting frequency for brands like Nike, Adidas, and Reebok, and compare categories by bar height for quality control insights.

Create a bar graph for qualitative data in Microsoft Excel by inserting a column chart, adding x-axis and chart titles, and formatting the axis.

Explore how to construct and interpret pie charts in Excel, including data arrangement, calculating shares in degrees, labeling, and design considerations such as 2D versus 3D charts.

Explore discrete data and learn how to present it with ungrouped and grouped frequency distributions, using a hotels example to condense raw data into clear class intervals.

Define clear, non-overlapping class intervals for a grouped frequency distribution, using five to twenty classes with equal sizes and unambiguous class limits.

Create an ungrouped frequency distribution for discrete data in Excel by using min and max to define the range, countif to tally occurrences, remove zero frequencies, and sort by frequency.

Learn to create a grouped frequency distribution for discrete data in Excel, using a manual approach and the data analysis toolpak to define class intervals and calculate frequencies.

Learn to build continuous frequency distributions by using inclusive and exclusive class intervals, excluding upper limits, with practical examples from sales data and addressing missing observations.

Learn to create simple and multiple bar graphs in Excel using quarterly sales data. Insert column charts, format axes and legends, and add data series to compare across years.

Learn to construct a histogram from a continuous frequency distribution using exclusive classes, interpret its shape and skewness, and understand steps to visualize data on sales and age.

Convert inclusive intervals to exclusive boundaries by filling gap between limits; compute lower boundary as lower limit minus D/2 and upper boundary as upper limit plus D/2 to construct histogram.

Learn to build a grouped frequency distribution for continuous data and create a histogram in Excel, using two methods with exclusive class boundaries and an example of 25 salesmen.

Learn to build less than and more than cumulative frequency distributions from a group frequency distribution, using upper and lower class limits, and compute cumulative relative frequencies and percent frequencies.

Assess how pie charts can be limited for comparing product sales and contrast them with a horizontal bar graph, and identify when pie charts effectively emphasize large or small shares.

Learn techniques to present data with graphs that capture attention using color intensity and three attentive attributes, with monthly sales examples and key-month emphasis.

explore building and interpreting frequency and less-than cumulative frequency distributions from clinic waiting times, using inclusive and exclusive class intervals, rounding rules, and relative percentages to reveal patient wait variation.

Explore numerical measures of central tendency for quantitative data, and learn how mean, median, and mode summarize data by a single value to identify the center.

Learn arithmetic mean, the measure of central tendency, computed as the sum of all observations divided by count, with X and N for population and x and n for sample.

Explore why the mean is a popular measure of central tendency: it uses all observations, is easy to calculate, and yields zero total deviation, unlike the median or mode.

Learn to compute the mean from ungrouped data by summing observations and dividing by the count, using a driving speed example and the ungrouped frequency distribution method.

Compute the mean for grouped data using the middle values of each class and frequencies, sum of fx, then divide by the total observations.

Learn how weighted mean accounts for unequal importance of observations, use the formula, and apply it to raw material purchases with varying quantities.

Learn how to compute the mean in Excel from raw, ungrouped, and grouped data, and how to calculate weighted mean using the sum and average functions.

Use driving speed data to illustrate how the median divides a distribution and how to compute it for odd and even sample sizes.

Explore the mode—the most frequent value—as a central tendency measure, illustrated with driving speed data and qualitative data usage, and note issues like multiple or no modes.

Compare mean, median, and mode to decide which measure to use based on data type and outliers; show how outliers and skewed data favor median, while mode suits qualitative data.

Calculate median and mode in Excel with median and mode, handle odd and even datasets without sorting, and learn how Excel shows the smallest mode when ties occur.