It's actually: I = PRT
I = Interest
P = Principle
R = Rate
T = Time
I think the number would be 1.
This question is incomplete. There are options in the question (from reference) and no highlight in the red bolded text in the question.
What effect does decreasing the temperature of a room have on a lifespan of a battery?
Which variable is highlighted in red, bolded tex?
a
. Independent
b
. Dependent
c
. Control
d
. None
But the answer to both the independent and dependent variables will be provided and explained in detail.
Answer:
Independent variable: decrease in temperature
Dependent variable: lifespan of battery
Step-by-step explanation:
The independent variable in an experiment is defined as the variable that can be changed or manipulated in order to find an outcome while the dependent variable is defined as the variable that is influenced by the changes in the independent variable.
In the given example, a decrease in temperature is the dependent variable as it is changing and the lifespan of battery is the dependent variable as it is responding to the independent variable ?9decrease in temperature).
Type I error says that we suppose that the null hypothesis exists rejected when in reality the null hypothesis was actually true.
Type II error says that we suppose that the null hypothesis exists taken when in fact the null hypothesis stood actually false.
<h3>
What is
Type I error and Type II error?</h3>
In statistics, a Type I error exists as a false positive conclusion, while a Type II error exists as a false negative conclusion.
Making a statistical conclusion still applies uncertainties, so the risks of creating these errors exist unavoidable in hypothesis testing.
The probability of creating a Type I error exists at the significance level, or alpha (α), while the probability of making a Type II error exists at beta (β). These risks can be minimized through careful planning in your analysis design.
Examples of Type I and Type II error
- Type I error (false positive): the testing effect says you have coronavirus, but you actually don’t.
- Type II error (false negative): the test outcome says you don’t have coronavirus, but you actually do.
To learn more about Type I and Type II error refer to:
brainly.com/question/17111420
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Hypotenuse by Pythagoras theorem = 407.83.
