It means tell them how your hypothesis was right or not.
It depends on whether the hypothesis concerns the mean or the standard error (or variance) or something else.
Before conducting an experiment, a math problem or series of calculations one usually writes down what their expectations are that a certain result will come from the calculations or experiments. This is called a Hypothesis. You then conduct the experiment or set of calculations, in order to find out whether your expectations, based on your estimations, were correct, or wrong.
You use a z test when you are testing a hypothesis that is using proportions You use a t test when you are testing a hypothesis that is using means
Scientists decide whether their data supports or refutes their hypothesis or prediction; they look for possible errors...
alternitive hypothesis
It must be possible to observe whether the hypothesis is true.
it mean to see if your hypothesis is correct
The null hypothesis is that there is no change in the population mean while the alternative hypothesis is that there is a change in the mean. The null hypothesis is stated as Ho:Mu=? in statistics while the alternative hypothesis is stated as Ho:Mu(<,>,≠)? depending on whether you are looking for mu to be greater, less than, or not equal to population mean.
It depends on whether the hypothesis concerns the mean or the standard error (or variance) or something else.
Tells you if you're hypothesis is correct or incorrect!!
Hypothesis is a guess with no proof. when proved, it is stated as phenomenon.
The hypothesis must be able to be proved true or false.
A conclusion is the analysis of your project. You typically look at your data, and compare it to your hypothesis and state whether your hypothesis was right or wrong. This is also where you states variables, and any errors that might have occurred, like improper mass, or improper calculations.
Before conducting an experiment, a math problem or series of calculations one usually writes down what their expectations are that a certain result will come from the calculations or experiments. This is called a Hypothesis. You then conduct the experiment or set of calculations, in order to find out whether your expectations, based on your estimations, were correct, or wrong.
You use a z test when you are testing a hypothesis that is using proportions You use a t test when you are testing a hypothesis that is using means
Do the experiment again and again to confirm the data is correct If the data is consistent then your hypothesis is wrong and you need to think of a new one that fits the data.
It means there is no reason why he should reject it, whether because there is no evidence to the contrary or because an experiment set up to test it affirmed that hypothesis.