Assignment On Simulation

From the above output, we can see that the p-value is 0.000186, which is smaller than 0.05 (if we select a 0.05 significance level).

All the p-values are greater than 0.05, therefore there is a statistical difference between each transect.

15 In testing the hypotheses: H0 β1 ’ 0: vs. H1: β 1 ≠ 0 , the following statistics are available: n = 10, b0 = 1.8, b1 = 2.45, and Sb1= 1.20. The value of the test statistic is:

We reject Ho if χ2 > χα2. At α=0.05, with 4 degrees of freedom, the critical value becomes χα2=9.488 (table E.4)

(21) You took a sample of size 21 from a normal distribution with a known standard deviation, . In order to find a 90% confidence interval for the mean, You need to find.

Decision Rule: The calculated test statistic of -3.024 does fall in the rejection region of z<-1.645, therefore I would reject the null and say there is sufficient evidence to indicate mu<50.

For d1, t-statistic=- 2.5334, t-statistic > t-critical. Thus we reject Ho and d1 is significant.

Data that is statistically significant helps us to understand whether there is a relationship within the null hypothesis. T statistical significant results showed that the participants who consumed caffeine performed worse than participants who did not was less than 5% (p < .05). This means for the author to determine whether a test is significant it must be less than .05, which is the significance level. The P value (probability value) is defined as the probability of obtaining a result equal to or "more extreme" than what was observed (Wikipedia). A p-value helps determine the significance

The largest number of customers belong to the Urban Location category (44%), followed by those in the

(d) In a hypothesis testing, if the p-value is less than the significance level α, we do not have

P-value represents a decimal between 1.0 to below .01. Unfortunately, the level of commonly accepted p-value is 0.05. The level of frequency of P>0.05 means that there is one in twenty chance that the whole study is just accidental. In other words, that there is one in twenty chance that a result may be positive in spite of having no actual relationship. This value is an estimate of the probability that the result has occurred by statistical accident. Thus, a small value of P represents a high level of statistical significance and vice

To test the null hypothesis, if the P-Value of the test is less than 0.05 I will reject the null hypothesis.

The next table shows the results of this independent t-test. At the .05 significance level, can we conclude

With a P-value of 0.00, we have a strong level of significance. No additional information is needed to ensure that the data given is accurate.

“The significance level associated with a statistical test indicates the probability with which this error may be made” (Iacobucci, 2009). In this case the significance level is .05. The probability of occurrence is .001, which means that it is lower and there is a lower chance of the statement not being true. In this case the null hypothesis should be rejected because it is lower than the significance level.