Answer:
C.) 7.14 in²
Step-by-step explanation:
The figure is made up of a square and a circle. The circle is divided in half and each piece is set on one side of the square. This means that the diameter of the circle is equal to the length of the sides of the square, 2 inches.
The area of the square can be found by multiplying length times the width:
The area of the square is 4 inches, and since we multiplied two lengths, we square the value:
A=4in²
Now find the area of the circle using the formula:
The radius is half of the diameter, so the radius is 1. Insert values and solve:
The area of the circle is equal to π. Add the values together:
The area of the figure is 7.14 in²
:Done
Answer:
1/52
Step-by-step explanation:
2 to the fourth is 16, and 6 to the second is 36. However, since it's a negative exponent, you'd have to move it down to to the bottom of the fraction, creating 1/16+36, which makes 1/52.
If it is perpendicular to the line 14x-7y=4, then we know our line has the opposite and inverse slope of that line. Solving for y of the first line, we get y=2x-(4/7). All we care about is the coefficient of the x term, because that will give us our slope. The slope of the first line is 2, so the slope of out line is the opposite and inverse of that slope, which -(1/2).
Plugging into our slope- point formula, where y1=(-9), x1=2, and m=(-1/2), then:
y-(-9)=(-1/2)(x-2)
y+9=(-1/2)x+1
y=(-1/2)x-8
Sampling errorThe natural discrepancy, or amount of error, between a sample statistic and its corresponding population parameter.distribution of sample means<span>The collection of sample means for all of the possible random samples of a particular size (n) that can be obtained from a population.</span>sampling distributionA distribution of statistics obtained by selecting all of the possible samples of a specific size from a population.central limit theorem<span>For any population with mean μ and standard deviation σ, the distribution of sample means for sample size n will have a mean of μ and a standard deviation of σ/√n and will approach a normal distribution as n approaches infinity.</span><span>expected value of M</span>The mean of the distribution of sample means is equal to the mean of the population of scores, μ, and is called this.<span>standard error of M</span><span>The standard deviation for the distribution of sample means. Identified by the symbol σ˯M. This standard error provides a measure of how much distance is expected on average between a sample mean (M) and the population mean (μ).</span>law of large numbers<span>States that the larger the sample size (n), the more probable it is that the sample mean is close to the population mean.</span>
8 x 5 = 40
40 hours = 2400 minutes
2400>2250
Keith spends more time at work
