Methods for Improving Measurement Reliability

Methods for Improving Measurement Reliability
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  • 0:06 Reliability
  • 2:00 Inconsistency
  • 3:27 Improving Reliability
  • 5:35 Lesson Summary
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Lesson Transcript
Instructor: Natalie Boyd

Natalie is a teacher and holds an MA in English Education and is in progress on her PhD in psychology.

Reliability is the consistency of the results of a measurement tool. But, what causes a tool to have low reliability? And, what can be done to improve reliability? In this lesson, we'll answer both of those questions.


Imagine that you wake up one morning and hop on the scale to see how much that chocolate cake you had last night is going to cost you in terms of weight. You look down at the scale, and it reads 100 lbs. 'That can't be right,' you think, 'I'm normally around 150 lbs.' Just to make sure, you step off the scale and step back on. This time, it says 184 lbs. Confused, you step off and back on, and it reads 137 lbs. What's going on?

Reliability is when a measurement tool consistently gives the same answer. If your scale tells you that you weigh 150 lbs every time you step on it, it is reliable. But, if it says 100 lbs one time, 184 lbs the next time, and 137 lbs the time after that, and nothing has changed, it is not reliable.

Why is reliability important? If a measure is not reliable, we cannot trust what it tells us. It's like being a manager and having an employee who never does what he's supposed to do. He comes in late, surfs Facebook instead of working, and doesn't ever tell the truth when you ask him questions. How can you trust and depend on him?

The same thing is true for measurement tools. If we have a survey that's supposed to measure sexism, we want it to consistently measure sexism. But, if it tells us that Johnny is sexist when he takes it one day and then it says he's not on the next day and Johnny hasn't had a personality change, then the survey is not reliable. As a result, we can't trust or depend on the results of the survey. Let's look closer at some things that cause measurement tools to be unreliable and some ways to improve the reliability of measures.


Let's go back to our sexism survey for a moment. We give the survey to Johnny, and the level of his sexism is different every time he takes it. One day it says he's sort of sexist, the next day it says that he's not sexist at all, and the day after that it says that he's the most sexist person who ever lived.

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