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at these points, you are going to use internet or any reference to collect data worth investigating from the government agencies (e.g., mean age of high school students dropouts, mean salaries employee), Formulate the null hypothesis and the alternative hypothesis for your data at hand. The scoring rubric will be used in assessing your performance.
WHAT YOU HAVE TO DO
1. Formulate the null and alternative hypothesis of the data you collected.
2. Identify whether the test to be administer in the data you have is directional or non-direction
3. Tell the possible type I and II error if a mistake in decision will be made.
Nonsence and wrong answers will be reported
at these points, you are going to use internet or any reference to collect data worth investigating from the government agencies (e.g., mean age of high school students dropouts, mean salaries employee), Formulate the null hypothesis and the alternative hypothesis for your data at hand. The scoring rubric will be used in assessing your performance.
WHAT YOU HAVE TO DO
1. Formulate the null and alternative hypothesis of the data you collected.
2. Identify whether the test to be administer in the data you have is directional or non-direction
3. Tell the possible type I and II error if a mistake in decision will be made.
Nonsence and wrong answers will be reported
Answers & Comments
Answer:
FORMULATE THE NULL AND ALTERNATIVE HYPOTHESIS OF THE DATA YOU COLLECTED
Step-by-step explanation:
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Verified answer
Answer:
1.The actual test begins by considering two hypotheses. They are called the null hypothesis and the alternative hypothesis.
2.Nothing much! If the study is a laboratory experiment then we can call the hypothesis “an experimental hypothesis”, where we make a prediction about how the IV causes an effect on the DV. If we have a non-experimental design, i.e. we are not able to manipulate the IV as in a natural or quasi-experiment , or if some other research method has been used, then we call it an “alternativehypothesis”, alternative
3.The probability of making a Type I error is the significance level, or alpha (α), while the probability of making a Type II error is beta (β). These risks can be minimized through careful planning in your study design.False-positive and false-negative results can also occur because of bias (observer, instrument, recall, etc.).
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