The test hypothesis using 0.05 significance level has the following results:The treatment means differ, The block means do not differ.
<h3>What is hypothesis testing?</h3>
A poll or study's findings can be tested using the statistical procedure known as hypothesis testing to see if the findings are significant. By calculating the likelihood that the findings happened by chance, you are basically evaluating if the findings are genuine. If it's possible that your results were a coincidence, the experiment won't be reproducible and won't be of much help.
Hypothesis testing may be one of the most perplexing components for students, mostly because you must first determine what your null is so that you can conduct a test. These challenging word problems that you encounter might sometimes be challenging to understand.
Make a plan for your null hypothesis.
Write down your null hypothesis
Determine the type of test you must do,
How to solve?
Describe the null and alternate treatment hypotheses:
Null hypothesis: No difference in treatment means
Alternative interpretation: The means differ
Indicate the treatment decision-making process:
F(1,2)=18.51 as seen in the table
Reject the null hypothesis if the estimated F exceeds 18.51.
Treatments Calculated F=43.75 > 18.51; hence, the null hypothesis is rejected.
As a result, we find that the treatment means differ.
Write out the null and alternative hypotheses for blocks.
Block means are not different under the null hypothesis.
A different theory There exists at least one pair of distinct meanings.
State the block decision rule as well:
Table F(2,2)=19.0 value
If the estimated F is greater than 19, reject the null hypothesis.
Blocks determined that F=8.14 19.0, thus we did not reject the null hypothesis.
Our conclusion is that the block means are equivalent.
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