If the p-value is smaller than the level of significance, then it indicates strong evidence against the null hypothesis, as there is less than a 5% probability the null hypothesis is correct.
In this question,
A p-value is a probability, calculated after running a statistical test on data and it lies between 0 and 1. The p-value only tells you how likely the data you have observed is occurred under the null hypothesis.
One of the most commonly used p-value is 0.05. If the value is greater than 0.05, the null hypothesis is considered to be true. If the calculated p-value turns out to be less than 0.05, the null hypothesis is considered to be false, or nullified (hence the name null hypothesis).
A small p-value (< 0.05 in general) means that the observed results are unusual, assuming that they were due to chance only. Now, the smaller the p-value, the stronger the evidence that should reject the null hypothesis.
Hence we can conclude that if the p-value is smaller than the level of significance, then it indicates strong evidence against the null hypothesis, as there is less than a 5% probability the null hypothesis is correct.
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Answer: 30%
Step-by-step explanation:
Given: Cupcakes have sprinkles = 15
Cupcakes didn't have sprinkles = 35
Total cupcakes = 15+35 = 50
The percentage of the cupcakes had sprinkles =
Hence, the percentage of the cupcakes had sprinkles = 30%
Answer:
A. (2,0)
Step-by-step explanation:
If you graph both of these equations, the two lines will intercept at point (2,0)
When you interpret a graph, the first you should read is the title.
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Answer:46%
Step-by-step explanation: