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abruzzese [7]
3 years ago
5

PLEASE HELP ME 30POINTS +BRAINLY

Mathematics
1 answer:
Serga [27]3 years ago
6 0

1) If a die is rolled once, determine the probability of rolling a 4: Rolling a 4 is an event with 1 favorable outcome (a roll of 4) and the total number of possible outcomes is 6 (a roll of 1, 2, 3, 4, 5, or 6). Thus, the probability of rolling a 4 is \frac{1}{6}.

If a die is rolled once, determine the probability of rolling at least a 4: Rolling at least 4 is an event with 3 favorable outcomes (a roll of 4, 5, or 6) and the total number of possible outcomes is again 6. Thus, the probability of rolling at least a 4 is \frac{3}{6} = \frac{1}{2}.

<h3>Here are two more examples: </h3>

If a coin is flipped twice, determine the probability that it will land heads both times:

Favorable outcomes: 1 -- HH

Possible outcomes: 4 -- HH, HT, TH, TT

Thus, the probability that the coin will land heads both times is \frac{1}{4}.

If Dan grabs one sock from a drawer containing 3 white socks, 4 blue socks, and 5 yellow socks, what is the probability that he will grab a white sock?

Favorable outcomes: 3 (3 white socks)

Possible outcomes: 12 (3 white socks + 4 blue socks + 5 yellow socks)

Thus, the probability that Dan will grab a white sock is \frac{3}{12} = \frac{1}{4}.

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5 0
3 years ago
18-23(if you want) I don’t understand what do, please help!
Tamiku [17]

Answer:

-22

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1.Factor out the negative sign.

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Hope this helps :)

3 0
3 years ago
Read 2 more answers
Listed below are the overhead widths​ (in cm) of seals measured from photographs and the weights​ (in kg) of the seals. Construc
Anarel [89]

Answer and Step-by-step explanation: Scaterplot is a type of graphic which shows the relationship between to variables. In this question, you want to determine if there is a linear relationship between overhead widths of seals and the weights. So, the hypothesis are:

H₀: no linear correlation;

H₁: there is linear correlation;

In this hypothesis test, to reject H₀, the correlation coefficient r of the data set has to be bigger than the critical value from the table.

With α = 0.05 and n = 6, the critical value is 0.811.

The linear correlation is calculated as:

r = n∑xy - ∑x.∑y / √[n∑x² - (∑x)²] [n∑y² - (∑y)²]

r = \frac{6.9632 - 51.1108}{\sqrt{6.439 - (51^{2} )}.6.14482 - (1108^{2} ) }

r = 0.9485

Since r is bigger than the critical value, H₀ is rejected, which means there is enough evidence to conclude that there is linear correlation between overhead widths and the weights.

In the attachments is the scaterplot of the measurements, also showing the relationship.

5 0
4 years ago
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