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Section 1.2: Measurement

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Section 1.2:Measurement

- Are the measurements valid?
- What would make them NOT valid?

- Are the measurements reliable?
- What would make them NOT reliable?

- Is there any bias in your data?
- What would create bias in this activity?

- A variable is a VALID measure of a property if it is relevant or appropriate as a representation of that property.
- Sometimes it is better to use a rate than a count.
- Percentages of population versus number of people in population.

- Example: Your study would not be valid if you measured the height of students in an attempt to study students’ math grades.

- How accurate does one variable predict another?
- Does a variable predict success to a given task?
- Example: Scores from IQ Tests are used to predict intelligence.

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True Weight

Scale stuck this morning and read a pound lower

Measured Value

Scale Reading

True

Value

Random Error

EXAMPLE: Bathroom Scale

Scale always reads 3 pounds higher

=

=

+

+

Bias

+

+

- Bias: When a measurement process systematically overstates or understates the true value.
- Example: When measuring everyone’s height, all rulers started at 1 inch, not 0 inches.

- Reliability: When there is a small random error after repeated measurements.
- A study is reliable if measurements are consistent!

- You want small variability (very little spread for your data).

- Find the most accurate method of measuring
- Repeat Measurements (obtain a larger sample)
- If possible, take the averages of measurement data to draw conclusions from!

- You take your blood pressure at home using a home monitor. You get the following results: 120/80, 132/90, 125/85, 110/70, 135/85. You go to the doctor and find that your actual blood pressure is 121/80.
-Is your blood pressure monitor a valid method for measuring your blood pressure? Explain.

- Does your BP monitor have a problem with reliability or bias? Explain.