I'm not really sure what the F-ratio is, but we just finished null and alternative ratios in our AP stats class. In our class, we calculuated a p-value, and if that value is smaller than the alpha-value (significance level) you have enough evidence to reject the null hypothesis. Sorry if this doesn't help.
Probability of rejecting a true null hypothesis; that is, the alpha value or risk you are willing to take probabilistically speaking.
You accept an alternative hypothesis when the p-value is greater than the sample a for a confidence level of 95%. The null hypothesis cannot be accepted.
A p-value is the probability of obtaining a test statistic as extreme or more extreme than the one actually obtained if the null hypothesis were true. If this p-value is less than the level of significance (usually set by the experimenter as .05 or .01), we reject the null hypothesis. Otherwise, we retain the null hypothesis. Therefore, a p-value of 0.66 tell us not to reject the null hypothesis.
The standard deviation for a set of data is a measure of how much the individual observations are spread about their mean. A small value indicates that they are all tightly packed around the mean value whereas a large value indicates that the observations are not so close together.
The critical value is used to test a null hypothesis against an alternative hypothesis at some pre-defined level of significance. A test statistic is calculated from the outcomes of a set of trials and if this test statistic is more extreme than the critical value then the null hypothesis must be rejected in favour of the alternative.
A large value for the chi-squared statistic indicates that one should be suspiciuous of the null hypothesis, because the expected values and the observed values willdiffer by a large amount
you do not need to reject a null hypothesis. If you don not that means "we retain the null hypothesis." we retain the null hypothesis when the p-value is large but you have to compare the p-values with alpha levels of .01,.1, and .05 (most common alpha levels). If p-value is above alpha levels then we fail to reject the null hypothesis. retaining the null hypothesis means that we have evidence that something is going to occur (depending on the question)
We have two types of hypothesis i.e., Null Hypothesis and Alternative Hypothesis. we take null hypothesis as the same statement given in the problem. Alternative hypothesis is the statement that is complementary to null hypothesis. When our calculated value is less than the tabulated value, we accept null hypothesis otherwise we reject null hypothesis.
a. the hypothesis ispartly true but needs to be revised. b. the hypothesis wrong. c. the hypothesis is supported. d. the hypothesis is of no value.
Probability of failing to reject a false null hypothesis.
Probability of rejecting a true null hypothesis; that is, the alpha value or risk you are willing to take probabilistically speaking.
When forming a hypothesis for quantitative research, a declarative hypothesis states the expected relation between variables, whereas a null hypothesis states that there is no significant relation.
In hypothesis testing, this is the probability of failing to reject a false null hypothesis.
When probability value (p-value) is greater than alpha value, we fail to reject the null hypothesis.Probablity value is the probability of obtaining an answer equal to or more extreme than the observed value.Alpha value is the level of significance. It's the value set that determines if a result is statistically significant, or in other words, if it's not likely to have occurred simply due to chance. Alpha value is usually 5%.There are two hypotheses when we conduct a hypothesis test: the null hypothesis and the alternative hypothesis.The null hypothesis acts as a default position. It's usually an assumption that there is no relationship between two events or that a treatment has no effect. In most legal systems, the null hypothesis would be that the defendant is innocent.The alternative hypothesis is what we would assume if we reject the null hypothesis. We reject the null hypothesis when the probability value is less than the alpha value.
You accept an alternative hypothesis when the p-value is greater than the sample a for a confidence level of 95%. The null hypothesis cannot be accepted.
0.5
yes the R-value does indicate resistance to heat flow