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To write repeated multiplication in an exponential notation, you should write the number that has to be multiplied as the base. Count the number of times that the number is used.
They should be repeated to make sure they work u retartd ! who askes that stupid quistion go home . YOLO(: BY : autumn parent
A minimum of 6 sets of data are needed to make a valid conclusion.
In statistics you have an experiment which will consist of one or more measurements. These measurements are converted to some statistic: it could be the sample mean, variance, maximum or something else. If you repeated the experiment, the value of this statistic would also change.If your hypothesis is true - whether in terms of the distribution or its parameters - and you repeated the experiment many times, you should expect the statistic to fall within the confidence interval (CI) in 95% of your trials. Even if the hypothesis is true, you should expect random variations to cause your statistic to lie outside the CI in 5% of cases.If you have a result that falls outside the 95% CI, it could be because you were unlucky and hit upon one of the 5% of rogue cases or that your hypothesis was incorrect. In this case you play the odds and conclude that your [null] hypothesis was incorrect.In statistics you have an experiment which will consist of one or more measurements. These measurements are converted to some statistic: it could be the sample mean, variance, maximum or something else. If you repeated the experiment, the value of this statistic would also change.If your hypothesis is true - whether in terms of the distribution or its parameters - and you repeated the experiment many times, you should expect the statistic to fall within the confidence interval (CI) in 95% of your trials. Even if the hypothesis is true, you should expect random variations to cause your statistic to lie outside the CI in 5% of cases.If you have a result that falls outside the 95% CI, it could be because you were unlucky and hit upon one of the 5% of rogue cases or that your hypothesis was incorrect. In this case you play the odds and conclude that your [null] hypothesis was incorrect.In statistics you have an experiment which will consist of one or more measurements. These measurements are converted to some statistic: it could be the sample mean, variance, maximum or something else. If you repeated the experiment, the value of this statistic would also change.If your hypothesis is true - whether in terms of the distribution or its parameters - and you repeated the experiment many times, you should expect the statistic to fall within the confidence interval (CI) in 95% of your trials. Even if the hypothesis is true, you should expect random variations to cause your statistic to lie outside the CI in 5% of cases.If you have a result that falls outside the 95% CI, it could be because you were unlucky and hit upon one of the 5% of rogue cases or that your hypothesis was incorrect. In this case you play the odds and conclude that your [null] hypothesis was incorrect.In statistics you have an experiment which will consist of one or more measurements. These measurements are converted to some statistic: it could be the sample mean, variance, maximum or something else. If you repeated the experiment, the value of this statistic would also change.If your hypothesis is true - whether in terms of the distribution or its parameters - and you repeated the experiment many times, you should expect the statistic to fall within the confidence interval (CI) in 95% of your trials. Even if the hypothesis is true, you should expect random variations to cause your statistic to lie outside the CI in 5% of cases.If you have a result that falls outside the 95% CI, it could be because you were unlucky and hit upon one of the 5% of rogue cases or that your hypothesis was incorrect. In this case you play the odds and conclude that your [null] hypothesis was incorrect.
you can't because you will not have the right results to the experiment.In order to make sure you are getting good results from an experiment you should conduct repeated trials, use only one control group, have as many individuals as possible in both the control group and the experimental group, and test only one independent variable at a time.Hope that helped!
why should an experiment be repeated
data from repeated trials of the experiment
Quantitative experiments should be repeated to make sure they are accurate. This also helps to get rid of outliers in the experiment.
An experiment which can be repeated and will yield the same results. Ex. If x+y=z in the experiement if you try the experiment again you should get the same result "z".
If , in the course of your experiment, you run repeated trials with differing results, it is necessary to ensure that only one variable is changing for each experiment. Recheck the data collected for errors.
I.What types of plants were used in the experiment?II.What was the experiment's control? III.Was the experiment repeated more than once?
as much data as possible can be colleced in the time availble
It is only science if it can be repeated, so yes, experiments do need to be repeatable in order for something to be proven. The results of the experiment should be comperable if something is to be learned.
Apex Experimental results are not reliable if they are not repeatable.
To write repeated multiplication in an exponential notation, you should write the number that has to be multiplied as the base. Count the number of times that the number is used.
The results of an experiment must be reproducible, meaning that they can be consistently obtained when the experiment is repeated by other researchers. Results should also be accurate, reflecting the true outcome of the experiment, and relevant to the research question being investigated. Additionally, results should be clearly presented and interpreted in the context of existing scientific knowledge.
In order for an experiment to yield useful data, it is necessary to have a carefully designed experimental setup that controls for variables, a clear research question or hypothesis to guide the experiment, and a sufficient sample size to ensure statistical significance. Additionally, the experiment should be replicable by other researchers to verify the results.