Answer:
2x-10=37
Bc a number is x and that is doubled with 10 subtracted from that to equal 37
Answer:
Type 1 error.
Step-by-step explanation:
H0 : μ = 5.1
H1 : μ ≠ 5.1
The Pvalue of the test = 0.003
Decision made by the researcher was conclude that mean weight is not as advertised, that is the researcher rejected the Null hypothesis.
However, when the Pvalue is < α - value , we reject the null ; The type of error the researcher could have made is that ; The mean weight may be truly as advertised, Hence, leading us to make a false positive error, thus is rejecting a true null. This is a TYPE 1 error.
Answer:
Step-by-step explanation:
(z - 5) (z +3)
z*z = z^2
z*3 = 3z
z^-5 = -5z
-5*3 = -15
z^2 + 3z - 5z - 15
<span>Make a the subject of the formula: ab-cd=ac hope this helps
Good luck.</span>
The standard deviation of what? Percentiles from any normal distribution look the same, just like the unit normal, so you can't really determine the standard deviation of the original scores. You can determine a z score from a percentile. That tells us the number of standard deviations, positive or negative, a given score is away from the mean score. It's a normalized test result.
Your percentile is (a hundred times) the probability that another score is less than your score. We have a normal distribution, so that probability is the integral of the standard normal from negative infinity to our normalized score.
Let's call the percentile rank
, already scaled between zero and 1.
corresponds to a z score
because the fiftieth percentile means we got an exactly average score, 0 standard deviations away from the mean.
We know 68% of the probability will be between -1 and +1 standard deviation. So
corresponds to
and
corresponds to
Similarly, 95% of the probability will be between -2 and +2 standard deviations. So
corresponds to
and
corresponds to
That's about the list I can do off the top of my head. I think three standard deviations is 99.7%. For the rest we just consult a z table or integrated normal table. We find p in the body of the table (maybe |.5-p| depending on the table) and then the column headings tell us our z score.
In this modern age, your computer can do this for you quickly