(-4/5) (15/8) (7/3) (-1)

What is 10,727,495 in expanded form and word form

lina2011 [118]

Hi, I think it might be: A) 10000000+700000+20000+7000+400+90+5 B) ten million, seven hundred and twenty seven thousand, four hundred and ninety five.

3 0

2 years ago

An object has a volume of 7cm³ and a mass of 56g. What is its density in g/cm³?

Nastasia [14]

Answer:8

Step-by-step explanation;Since you want to find the density but you already have the mass you do the inverse operation and divdie 56 by 7 and get 8.

5 0

2 years ago

Faced with rising fax costs, a firm issued a guideline that transmissions of 10 pages or more should be sent by 2-day mail inste

Volgvan

Answer:

a) The calculated value t = 5.903 > 2.572 at 0.01 level of significance

Null hypothesis is rejected at 0.01 level of significance

There is a true mean value is less than 10

b) p - value 0.00001

The p - value 0.00001 < 0.01

The result is significant at p<0.01

Step-by-step explanation:

Step(i):-

Given mean of the population = 10

Sample size 'n'= 35

Mean of the sample x⁻ = 14.44

Standard deviation of the sample 's' = 4.45

Level of significance ∝ = 0.01

Step(ii):-

Null Hypothesis H₀ : μ >10

Alternative Hypothesis : H₁ : μ < 10

Test statistic

$t = \frac{x^{-} -mean}{\frac{S}{\sqrt{n} } }$

$t = \frac{14.44-10}{\frac{4.45}{\sqrt{35} } }$

t = 5.903

Degrees of freedom = n-1 = 35-1 = 34

tabulated value t₀.₀₁,₃₄ = 2.572

The calculated value t = 5.903 > 2.572 at 0.01 level of significance

Null hypothesis is rejected at 0.01 level of significance

There is a true mean value is less than 10

p- value :

p - value 0.00001

The p - value 0.00001 < 0.01

The result is significant at p<0.01

8 0

2 years ago

Lengths of full-term babies in the US are Normally distributed with a mean length of 20.5 inches and a standard deviation of 0.9

mash [69]

Answer:

66.48% of full-term babies are between 19 and 21 inches long at birth

Step-by-step explanation:

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the z-score of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Mean length of 20.5 inches and a standard deviation of 0.90 inches.

This means that $\mu = 20.5, \sigma = 0.9$