JocquettaLARuex said:In a left-tailed test, the value of the test statistic is -2. If we know the shaded area is 0.03,
then we have sufficient evidence to reject the null hypothesis at 0.05 level of significance.
A left-tailed test is a statistical hypothesis test that is used to determine if the observed data is significantly lower than the expected value. It is used to test whether a sample mean is significantly less than a hypothesized population mean.
Rejecting the null hypothesis at 0.05 level means that the results of the statistical test have shown that there is enough evidence to reject the null hypothesis, and that the observed data is significantly different from the expected data at a significance level of 0.05 or 5%. This means that there is a 95% confidence that the results are not due to chance.
A null hypothesis is a statement that assumes there is no significant difference between the observed data and the expected data. It is typically represented as H0 in statistical tests and is used as a starting point for testing the alternative hypothesis.
The significance level, also known as alpha (α), is typically chosen before conducting the statistical test. It is based on the level of confidence needed in the results. A common significance level is 0.05 or 5%, which means there is a 95% confidence that the results are not due to chance.
When the null hypothesis is rejected, it means that there is enough evidence to support the alternative hypothesis. This means that the observed data is significantly different from the expected data and that the results are not due to chance. It does not necessarily mean that the alternative hypothesis is true, but rather that the null hypothesis is highly unlikely to be true.