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How to write repeated multiplication of a factor by using an exponent?
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.
Why should exsperiments be repeated?
They should be repeated to make sure they work u retartd ! who askes that stupid quistion go home . YOLO(: BY : autumn parent
What is the minimum number of data points an experiment should gather?
A minimum of 6 sets of data are needed to make a valid conclusion.
What is the 95 percent confidence interval for statistics?
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.
Why can't you test more than one variable in an experiment?
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!
