To find how the mean is affected by an outlier, we can find the means for both of the data sets. We can find a mean by adding all of the quantities together and then dividing by how many there are. But, instead since we see that the outlier is much larger, we know that it would make the data set's mean much larger, since by adding a number that is much greater than the rest, the dividing will create an even larger number.
No. This is because the two smaller lengths must be greater than the largest length (7+3=10) this is less than 13 meaning the triangle won’t work
Answer:
Conclusion : People ≠ 20% don't know about their credit score.
Step-by-step explanation:
Hypothesis is testing a statement for its statistical significance.
Null Hypothesis (H0) implies 'no difference from tested value', Alternate hypothesis (H1) implies 'significant difference from tested value'
Let % of people knowing their credit score = CS
H0 : CS = 20
H1 : CS ≠ 20
If the null hypothesis is rejected, it implies that we reject the claim that CS i.e '% of americans knowing their credit score = 20%'. So, the alternate hypothesis is accepted, i.e we conclude that '% americans knowing their credit score ≠ 20%'.
