Statistics: Statistical Significance and Null Hypothesis

In summary, the conversation discusses the definition of statistical significance at the 0.05 level, with one person asking for clarification on whether a student's explanation of it being a 0.05 probability for the null hypothesis to be true is correct. They also mention cross-posting and gender assumptions.
  • #1
jlo2006
3
0
Heres the problem:

When asked to explain the meaning of "statistically significant at the 0.05 level," a student says, "This means there is only probability 0.05 that the null hypothesis is true." Is this an essentially correct explanation of statistical significance? Explain.


Help please. Appreciated.
 
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  • #2
Can you perhaps mention some of your thoughts as to what the answer might be?

If you are finding it difficult to answer that, try to answer this: what is the definition of stat. significance?

Reading this might help.
 
Last edited:
  • #3
He already posted the same question in the statistics forum.
 
  • #4
How do you know it's a he? Jay-Lo? Hello?
 
  • #5
Ahh... of course I assumed he meant his name to be pronounced with a soft j, like "halo," and all Halo aficionados are male.

No, I'm kidding, I didn't notice the name.
 
  • #6
Regardless of gender, jlo2006 should not have cross-posted.
 

What is statistical significance?

Statistical significance is a measure of the likelihood that a result is not due to chance. It indicates whether the observed relationship or difference between variables is real and not just a random occurrence.

How is statistical significance determined?

Statistical significance is determined by calculating a p-value, which represents the probability of obtaining the observed result if the null hypothesis is true. A p-value of less than 0.05 is typically considered statistically significant, meaning that the observed result is unlikely to occur by chance alone.

What is the null hypothesis in statistics?

The null hypothesis is a statement that assumes there is no significant relationship or difference between variables. It is the default position that will be rejected if there is enough evidence to support an alternative hypothesis.

Why is the null hypothesis important in statistical analysis?

The null hypothesis is important because it provides a baseline for comparison in statistical analysis. By assuming there is no significant relationship or difference between variables, we can determine if the observed result is truly significant or just a chance occurrence.

What are some limitations of statistical significance?

Statistical significance is not the same as practical significance, which refers to the magnitude of the observed effect. A result can be statistically significant but not clinically or practically significant. Additionally, statistical significance does not prove causation, only correlation. Other factors may be influencing the relationship between variables.

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