Suppose the results indicate that the null hypothesis should be rejected; thus, it is possible that a type i error has been committed. given the type of error made in this situation, what could researchers do to reduce the risk of this error? increase the sample size. choose a 0.01 significance level instead of a 0.05 significance level.

You need to Choose a 0.01 significance level , instead of 0.05 significance level.

Step-by-step explanation:

Consider the provided information.

It is given that type I error has been committed.

Type I error occur, if we rejected the null hypothesis even null hypothesis is true.

We reject the null hypothesis if p-value < α

Accept the null hypothesis if p-value ≥ α

According to given condition the value of α is 0.05  that means 95% chance that your assumption is correct and 5% chance that assumption is wrong.

In order to reduce the risk of this error you need to increase the significance level so that the value of α becomes lower than the p value.

lower α means you will be less likely to detect a true difference if one really exists.

Hence, you need to Choose a 0.01 significance level , instead of 0.05 significance level.

you can't solve x because it is 2 linear equation and you only have one equation

24+x=y

step-by-step explanation: