Statistics is not about getting accurate results. It is about Finding sufficient evidence to prove that your null hypothesis (Ho) is correct Gathering data about the population Finding sufficient evidence to prove that your null hypothesis statement is wrong

State why a non-significant outcome does not mean the null hypothesis is probably true?

2. Can hypothesis testing ever prove a hypothesis true? How should we interpret an experiment where we fail to reject the null hypothesis?

What does it mean when sample results are statistically significant?

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In Chapter 17 Data Set 5, you will find entries for two variables: age category (young, middle-aged, and old) and strength following weight training (weak, moderate, and strong). Are these two factors independent of one another?                     Strength Weak Moderate Strong Age Young 12 18 22 Middle 20 22 20 Old 9 10 5         What is the null hypothesis in words?  (You will need to get this from lecture and/or the lecture notes. It is not covered in your text).       What is the alternative hypothesis in words? (See note in a. above)       What is your degrees of freedom for the test? How did you arrive at this answer?       Based on c. above and using an alpha =.05, what is the critical value for the test?       Use PSPP/SPSS to calculate the Chi Square value. Use the instructions on pages 304-305. Copy/paste the output table. (result in the pictures)       What is the Chi Square value? What is the p-value?       Based on f., do…

What does it mean when we reject the null hypothesis? What conclusion do we make, etc.? Explain in as much detail as you can

The smaller the observed p-value, the more evidence you have against the null hypothesis. Select one: True False

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Which of the following relates to the rejection of the null hypothesis when it is actually false? 1. Type I error 2. Type II error 3. Power 4. Statistical significance