hypothesis test Archives - Accendo Reliability

Hartley’s Test for Variance Homogeneity

The Hartley test is an extension of the F distribution-based hypothesis test checking if two samples have different variances.

The F test works with two samples allowing us to compare two population variances based on the two samples. This test does not work for three or more populations. We could conduct multiple pairwise comparisons, yet the probability of an erroneous result is significant.

Bartlett’s Test and Levene’s Test are non-parametric checks for homogeneity of variances. Bartlett’s Test pretty much expects the underlying data to be normally distributed.

Levene’s Test is a better choice when you’re not sure the data is normal. Both are conservative and time-consuming to calculate.

We need another way to check for equal variances. [Read more…]

by Fred Schenkelberg 2 Comments

Hypothesis Test Selection

Over the past few weeks, we have explored about 8 different hypothesis test formulas. There are more. So, how do you determine which test to perform? Well, that depends on the question you are trying to answer and the type of data you’re dealing with. [Read more…]

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The Paired-Comparison Hypotheses Test for Variances

The F-test provides a means to compare paired data variances. It is a variance hypothesis test.

If we are exploring the precision of one measuring device or another, or we are comparing assembly processes, we often want to know if the variance is different or not.
Working with data from normal distributions from two different processes or devices, we know from statistical theory that the ratio (s1)2 / (s2)2 is described by the F distribution.
There are three hypothesis test possible, basically to test if the population variances are different, or one is less than or greater than the other. The following details the three test’s null and alternative hypotheses. [Read more…]

by Fred Schenkelberg 1 Comment

Hypothesis Tests for Variance Case I

Statistics is the language of variation. Everything varies, and we use variance (σ²) to describe the spread of the data. For any experimental work aimed at making improvements, whether in the design, manufacturing process or field performance, there are two ways to make improvements. Move the center of the distribution, or reduce the spread of the data. [Read more…]

by Fred Schenkelberg 1 Comment

Degradation Hypothesis

This week I received a question from the ASQ Librarian concerning a person’s question about one of the CRE Question bank questions. It was a nice two-part question concerning a hypothesis test of a sample means value and degradation.

Here’s the question as sent over for consideration. [Read more…]

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Hypothesis Test Sample Size

Hypothesis testing permits us to compare two groups of items and determine if there is a significant difference or not. There are many types of hypothesis tests depending on the specific question, type of data, and what is or is not known when designing the test. [Read more…]