What is 3/8 x 16 for maths homework?

1 answer:

6 0

(a/b) times (c/d)=(ac)/(bd)
16=16/1

(3/8) times (16/1)=(3 times 16)/(8 times 1)=48/8=(2/2)(2/2)(2/2)(6/1)=(1)(1)(1)(6)=6

answer is 6

You might be interested in

A 12-sided die is rolled. The set of equally likely outcomes is {1 comma 2 comma 3 comma 4 comma 5 comma 6 comma 7 comma 8 com

LenKa [72]

Answer:

Step-by-step explanation:

It is certain that the number rolled will be less than 14, so the probability is 1.

7 0

3 years ago

Read 2 more answers

Here are summary statistics for randomly selected weights of newborn girls: nequals=174174, x overbarxequals=30.930.9 hg, seq

MaRussiya [10]

Answer:

The 95% confidence interval would be given by (29.780;32.020)

Step-by-step explanation:

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".

The margin of error is the range of values below and above the sample statistic in a confidence interval.

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

$\bar X=30.9$ represent the sample mean for the sample

$\mu$ population mean (variable of interest)

s=7.5 represent the sample standard deviation

n=174 represent the sample size

The confidence interval for the mean is given by the following formula:

$\bar X \pm t_{\alpha/2}\frac{s}{\sqrt{n}}$ (1)

In order to calculate the critical value $t_{\alpha/2}$ we need to find first the degrees of freedom, given by:

$df=n-1=174-1=173$

Since the Confidence is 0.95 or 95%, the value of $\alpha=0.05$ and $\alpha/2 =0.025$ , and we can use excel, a calculator or a tabel to find the critical value. The excel command would be: "=-T.INV(0.025,173)".And we see that $t_{\alpha/2}=1.97$ , this value is similar to the obtained with the normal standard distribution since the sample size is large to approximate the t distribution with the normal distribution.