Two eventis are independent if knowledge about the first doesn't change your expectation about the second.
a) Independent: After you know that the first die showed 4, you stille expect all 6 numbers from the second. So, the fact that the first die showed 4 doesn't change your expectation about the second die: it can still show numbers from 1 to 6 with probability 1/6 each.
b) Independent: It's just the same as before. After you know that the first coin landed on heads, you still expect the second coin to land on heads or tails with probability 1/2 each. Knowledge about the first coin changed nothing about your expectation about the second coin.
a) Dependent: In this case, there is a cause-effect relation, so the events are dependent: knowing that a person is short-sighted makes you almost sure that he/she will wear glasses. So, knowledge about being short sighted changed your expectation about wearing glasses.
Answer:
10 its just 10 or smthing
Answer:
30feet
Step-by-step explanation:
5 x 6 =30
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<h3>
Answer: x = 65.4</h3>
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Work Shown:
cos(angle) = adjacent/hypotenuse
cos(x) = 5/12
x = arccos(5/12)
x = 65.375681647836 which is approximate
x = 65.4 after rounding to one decimal place
Make sure your calculator is in degree mode. The arccosine function is the same as the inverse cosine function (shortened to 
).
Answer:
<em>In statistics, linear regression is a linear approach to modelling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables). The case of one explanatory variable is called simple linear regression. For more than one explanatory variable, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable.</em>
