Answer:
86.64%
Step-by-step explanation:
Mean (μ) = 220
σ= 16
n= 4
mean score(X) = 220 -12
= 208
Using central limit theorem which says that for a sample of size (n), the standard error is
standard deviation /√n
= 16/√4
= 16/2
= 8
Standard error = 8
Using Z score
Z = (μ - x) / standard error
Z= (220 -208)/8
Z= 12/8
Z= 1.5
From the table, Z = 1.5 = 0.4332
Since the normal distribution curve is symmetrical, we have
0.4332*2
= 0.8664
Percentage = 0.8664*100
= 86.64%
1 ten 16 ones=1*10+16*1=10+16=26
Hope this helps!
Answer:
(B) f(-4)=g(-4) and f(0)=g(0)
Step-by-step explanation:
From the given graph, the lines f(x) and g(x) intersects at two different points.
- When x=-4, f(-4)=4 and g(-4)=4
- When x=0, f(0)=4 and g(0)=4
Therefore, the points which represent where f(x)=g(x) are:
- f(-4)=g(-4); and
- f(0)=g(0)
The correct option is B.
The very first thing to do in every correlation activity is to plot the gathered data points in a scatter plot. It is better to use software tools like MS Excel because they have a feature there that uses linear regression like that one shown in the picture.
Once you plot the data points, make a trendline. You are given with options. If you want a linear function, then you will have a linear model with a function equation of y = 0.2907x + 2.2643. It has a correlation coefficient of 0.9595. That's a strong correlation already. The R² value tells how good your model fits the data points. If you want to increase the R², a better model would be a quadratic function with the equation, y = -0.0209x²+0.506x+2.0232. As you can see the R² increase even more to 0.9992.