PROBLEM SOLVING TOOLS: HISTOGRAM

PROBLEM SOLVING EDUCATION SERIES-PART 8

INTRODUCTION

Histogram is a graphical summary of a set of data that describes the amount of variation in a process. A histogram is the most commonly used graph to show frequency distributions. It looks very much like a bar chart, but there are important differences between them. This helpful data collection and analysis tool is considered one of the seven basic quality tools.​

WHEN TO USE HISTOGRAM?

• Numerical Data
• When we want to know if the data is normally distributed.
• Analyzing if a process meet customer requirements.
• Determine if a process change have occurred.

HOW TO CREATE A HISTOGRAM

1. Determine the type of data to collect. Make sure the data area measurable. Time, lengths and speed are examples.
2. Collect the data. Data collection shall be random.  collect as many measutabe points s possible.
3. Determine the number of interval required. USe this guide to determine how many intervals( or bars) the graph should have.
4. Determine the range. Subtract the smallest value from the largest. This value is the range of the data set.
5. Determine the interval width. Divide the range by the number of intervals. Round answers up to a convenient value. For example, if the range of data is 17 and 9 is the interval, the interval width is 1.88. Round the interval to 2.
6.  Determine the starting point of each interval. Use the smallest data point value as the starting point of the first interval. The starting point for the second interval is the sum of the smallest data point plus the interval width. For example, if the smallest data point is 10 and the interval width is 2, then the starting point for the second interval is 12. Label intervals along the horizontals.
7. Plot the data. Count the number of data points that fall within each interval. Plot this frequency on the histogram. Remember: each data point can appear in just one interval. For example, if the first interval begins with 10 and the second with 12, then all data points that are equal to or greater than 10.0 and still less than 12.0 are counted in the first interval.

HISTOGRAM ANALYSIS

​Before drawing any conclusions from your histogram, be sure that the process was operating normally during the time period being studied. If any unusual events affected the process during the time period of the histogram, your analysis of the histogram shape likely cannot be generalized to all time periods.