10 is the default base for a logarithm
log of 50 is equal to log base 10 of 50
Hello! For this you are just going to do this step by step, and remember to use PEMDAS. That is the order in which you should do the math. The abbreviation stands for Parenthesis, exponents, multiplication, division, addition and subtraction. So lets get started!
<span><span>(<span><span><span><span>(<span><span><span><span><span>15<span>y0</span></span><span>x<span>−3</span></span></span><span>z2</span></span>3</span><span>x3</span></span>)</span><span>(<span>y7</span>)</span></span><span>z1</span></span>2</span>)</span>2</span><span>=<span><span><span>254</span><span><span><span>x6</span><span>y14</span></span><span>z6</span></span></span><span>x6</span></span></span><span>=<span><span>254</span><span><span>y14</span><span>z6</span></span></span></span>
Hope this helps!! If you need any more help or further explanation just let me know!! :)
8n+3+9n+7=180
17n+10=180
17n=170
Answer
N=10
Answer:
Step-by-step explanation:
Hello!
The definition of the Central Limi Theorem states that:
Be a population with probability function f(X;μ,δ²) from which a random sample of size n is selected. Then the distribution of the sample mean tends to the normal distribution with mean μ and variance δ²/n when the sample size tends to infinity.
As a rule, a sample of size greater than or equal to 30 is considered sufficient to apply the theorem and use the approximation.
X[bar]≈N(μ;σ²/n)
If the variable of interest is X: the number of accidents per week at a hazardous intersection.
There is no information about the distribution of this variable, but a sample of n= 52 weeks was taken, and since the sample is large enough you can approximate the distribution of the sample mean to normal. With population mean μ= 2.2 and standard deviation σ/√n= 1.1/√52= 0.15
I hope it helps!
