Olive Ranch Olive Oil

profit by entering that market. If your bikes are not of higher quality than the average bike already in the market, you will make a loss by entering the market for bikes. You test, at the 5% level of significance, the hypothesis that the quality of your bikes exceeds the average quality of existing bikes in the market. Given this information, answer the following questions. (a) What would a Type I Error be in the context of this case? Explain what the consequences of a Type I Error would be. (2 marks) (b) What would a Type II Error be in the context of this case? Explain what the consequences of a Type II Error would be. (2 marks) (c) After conducting the test, you conclude that there is sufficient evidence in the data you observe to support the alternative hypothesis that

6. Based on the data, was the hypothesis supported, and what can you conclude from this experiment?

It tells that the t-statistic with 97 degrees of freedom was 2.14, and the corresponding p-value was less than .05, specifically around 0.035. Therefore, it is appropriate to conclude the research study was statistically significant.

“Hypothesis testing is a decision-making process for evaluating claims about a population” (Bluman, 2013, p. 398). This process is used to determine if you will accept or reject the hypothesis. The claim is that the bottles contain less than 16 ounces. The null hypothesis is the soda bottles contain 16 ounces. The alternative hypothesis is the bottles contain less than 16 ounces. The significance level will be 0.05. The test method to be used is a t-score. The test statistic is calculated to be -11.24666539 and the P-value is 1.0.  The P-value is the probability of observing a sample statistic as extreme as the test statistic, assuming the null hypothesis is true. The T Crit value is 1.69912702. The calculations show there is enough evidence to support the claim that the soda bottles do

Type 1 error was minimized by the researchers by their setting their significance level (alpha) at 0.05. Using this significance level is important since it is the minimal acceptable alpha level used in research and minimizes the risk of a Type 1 error (rejecting a null hypothesis that is true) ( Polit & Beck, 2014).

2. Give one possible two-tailed hypothesis that the authors may have had for this study (for one IV and one DV only) [2 points] .

"Inferential statistics is drawing conclusions of large data sets called a population" (Jaggia & Kelly, 2014). To analyze inferential statistics, I use regression analysis. "Regression analysis is used to examine the relationship between two or more variables" (Jaggia & Kelly, 2014).

1. The null hypothesis reveals the difference of data between 2010 and 2012, is consistent for all the math equations. H0: Mu = 119,155 2. The data from the readers in 2012, reveals that the alternative hypothesis is greater than 119,155, due to the difference in readers from 2010.

After forming the hypothesis, the errors that can occur with respect to the hypothesis are:

12. Which conclusions appear to be well supported by the pattern of results; and which conclusions do not appear to be well

prevalent. However, this magnitude of error does have its sources. Some of the sources are given below:

For a long time, and at times a detriment to us as psychological scientists, we have looked at evidence as a dichotomous significance decision. In other words, significance is viewed as anti-null or pro-null depending on the value of p. A p value less than .05 can mean success, yet a p value greater than .05 can mean failure, especially when we consider publications typically disregard non-significant results for publication. While there are very valid reasons for using that key number of .05 to determine significance, we could use .06 just as well. This is evident in other scientific fields. When looking at significant and non-significant differences, values can vary between extremes due to no sharp line between the differences.

The first step one must take when testing a hypothesis is restating the question experience analyzed into an alternative hypothesis and null hypothesis. The following scenario is as follows: “Do

Stang, Poole and Kuss explain, in SST, P-value is an important part to decide the null hypothesis. The SST itself, they explain is analytical approach that developed based on two prominent statisticians, Fisher and the Neyman-Pearson. However, in present practical, SST is incompatible amalgamation of those two theories. In Fisher theory, P value represents the strength of evidence against the null hypothesis: the lower the P-value, the stronger the evidence. In this theory, they criticize lake of alternative hypothesis and concept of statistical power. In contrast Neyman and Person theory included the alternative for the null hypothesis, type I and II error and theoretical of effect size. This hybrid method leads to

The team’s null hypothesis or (HO) is that white pay wages are ≥ Hispanic pay wages. The teams alternative hypothesis or (H1) is White pay wages are < Hispanic pay wages.