REPLY
Answer questions Minimum 100 words each and reference (questions #1-2) KEEP questions WITH ANSWER
1. A key point to get out of this topic is the idea that these errors are theoretical. You won't be sure as to whether one occurred or not. Why are they theoretical in nature? Hint: think about a study and knowing the "truth"
2. Pick a study of interest and identify the null and alternative hypothesis. How does this fit in with regards to the topic of a type I and type II error? Always keep this in mind when you are trying to identify what a type I and type II error are.
A minimum of 75 words each question and References (IF NEEDED)(Response #1 – 7) KEEP RESPONSE WITH ANSWER
Make sure the Responses includes the Following: (a) an understanding of the weekly content as supported by a scholarly resource, (b) the provision of a probing question. (c) stay on topic
1) According to the reading, we set the alpha which is the largest probability for type I error. To increase the power of a hypothesis researchers can use larger samples which provides more information and raise the significance level which increases the probability that the hypothesis will be rejected.
2) A Type 1 error occurs when individuals involved in research make the decision to reject the belief of truth when in actuality the hypothesis is true. Type 1 errors are errors in research when the researcher makes the wrong decision to reject a true null hypothesis. Type II errors are considered less of a problem than Type 1 errors, but can prove to be detrimental in the field of medicine. This type of error occurs when researchers decide to keep a false null hypothesis, when in fact the hypothesis is true. The method to avoid making Type 1 decisions is to test the null hypothesis at the highest level (Alpha Level). This will lessen the possibilities of making this type of error (Privitera, 2018).
3) According to Privitera (2018) a type 1 error is the probability of rejecting a null hypotheses that is actually true, researchers purposely make this error. A null hypotheses is a statement about a population parameter that is assumed to be true, this hypotheses is a starting point (Privitera, 2018). The type 2 error or beta error is the probability of retaining a null hypotheses that is actually false (Privitera, 2018). The type 1 error is committed when a researcher decides to reject previous notions of truth that are in fact true (Privitera, 2018). The best way to avoid these types of errors is to be open minded and not reject notions if there is fact to back the notions up. In my opinion a type 1 error is something committed with bias by the researcher. I say this because as a researcher it is their job to find all facts or at least most all facts and apply them to their study or research, especially if they commit a type one error knowingly. If a researcher does this error then they are not following through with basic research guidelines.
4) A one-tailed test is used in a hypothesis test where the alternative hypothesis is stated as either (>) or (<). When a researcher is interested in a specific alternative to the null hypothesis. A two-tailed test is used when one wants to avoid making a type III error. An error that occurs when one accepts a null hypothesis that is incorrect because the the rejection region of the tail was on the opposite end. SPSS can be used to compute the calculations for each by imputing data in to a new data chart and then using the frequencies tab to help solve for the mean and standard deviation. From there one can use appendix c. to solve for the two-tails. (Privitera., G. J., 2018).
5) We use the one-tailed test when we need to check or test the claim or hypothesis which is directional in nature. This means if the alternative hypothesis of the test includes ‘less than’ or ‘greater than’, then we use one-tailed tests. We use the two-tailed test when we need to check or test the claim or hypothesis which is non-directional in nature (Privitera., G. J., 2018). That is, if the alternative hypothesis of the test includes ‘not equal to’, then we use two-tailed tests. When we perform one-tailed tests and two-tailed test by using SPSS, then we need to use some setting or calculations. For most of the tests, SPSS provides the results for the two-tailed test as a default. Most of the times, SPSS do not provide results for one-tailed tests and in such cases, we need to calculate the p-value from this output.
Examples of one tailed and two tailed test is given as below:
H0: µ = 10 v/s Ha: µ < 10 (One tailed /lower tailed /left tailed /directional test)
H0: µ = 10 v/s Ha: µ > 10 (One tailed /upper tailed /right tailed /directional test)
H0: µ = 10 v/s Ha: µ ≠ 10 (two tailed /non-directional test)
6) In the Type 1 error and Type 2 error, in this two types of errors that exist in a hypothesis testing of Type 1 and Type 2. In Type 1 and Type 2 that occur in when the null hypothesis is true but is still being rejected. In being able to use the following example from a law case, this is equivalent of convicting an innocent man or individual. In the statistics or research types of errors in types think that he or she has a significant difference, when there is actually no significant differences in the types of errors. A Type 2 error occurs when null hypothesis is false but not rejected, which is equivalent of acquiring a guilty man or individual. This is where the researchers actually has a significant difference but does not realize it. Many examples are generated in the Type 1 and Type 2 that allows the researcher to understand and generate this hypothesis. In the law, example that is a matter of opinion and often depends on the nature of the time and associated in the factor that generates the punishment for the individual that committed the crime. That is why it is important to understand the meaning, understanding and hypothesis of this type 1 and type 2 significant of errors. In the statistics, replication of studies will reduce the chance that an artifact appears significant when it is not. In one type of error is eliminated and there is a very good chance of the other occurring. In the chance of both types of errors cannot be eliminated. There are many factors that allows the reseacher to come up with this type of hypothesis that allows them too see and understand this type 1 and type 2 errors.