Answer:
6.2%
Step-by-step explanation:
For each time the coin is tossed, there are only two possible outcomes. Either it is heads, or it is not. The probability of a toss resulting in heads is independent of other tosses. So we use the binomial probability distribution to solve this question.
Binomial probability distribution
The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.
In which 
is the number of different combinations of x objects from a set of n elements, given by the following formula.
And p is the probability of X happening.
Fair coin:
Equally as likely to be heads or tails, so 
Lorelei tosses a coin 4 times.
This means that 
.
What is the probability of tossing four heads?
This is P(X = 4).
0.062 = 6.2% probability of tossing four heads
A strong positive correlation.
Step-by-step explanation:
The question requires you to calculate the correlation coefficient and then make a conclusion about its value.
Form a table as shown where x is cost of items and y is shipping cost
x y xy x² y²
25 5.99 149.8 625 35.9
45 8.99 404.6 2025 80.8
50 8.99 449.5 2500 80.8
70 10.99 769.3 4900 120.8
190 34.96 1773.2 10050 318.3 ------sum
The formula for correlation coefficient follows;
r=n(∑xy)-(∑x)(∑y) ÷ √{[n∑x²-(x)²] [n∑y²-(y)²]}
where n=4
r=4(1773.2)-(190)(34.96) ÷ √{[4(10050)-190²] [4(318.3)-34.96²]}
r=450÷ √{4100*51)
r=450÷√209100
r=450÷457.3
r=0.98409
The value of r indicates a stronger positive correlation
Learn More
Correlation coefficient :brainly.com/question/12528676
Keywords :shipping costs,cost of items, strength of the model
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First, we should calculate the length in millimeters for the blueprint for each 1 meter.
33 ÷ 8 = 4.125
So, each 1 meter represents 4.125 mm on the blueprint.
Now, we can use this rate to calculate the length of blueprint if the length in real life is 6 meters. Multiply the actual length by the rate.
6 x 4.125
=24.75mm
Therefore, the length of the blueprint should be 24.75 millimeters.
Answer:
c. observed values of the independent variable and the predicted values of the independent variable
Step-by-step explanation:
This helps us, for example, find the values of y in a y = f(x) equation. y is dependent of x. So x is the independent variable and y the dependent. Obviously, this system is used for way more complex equations, in which is hard to find an actual pattern for y, so we use this method to compare the predicted values of y to the observed.
The correct answer is:
c. observed values of the independent variable and the predicted values of the independent variable
