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3 years ago

What is the probability of rolling a die and it landing on a number less than 3?

Mathematics

2 answers:

Paraphin [41]3 years ago

6 0

Answer:

The answer would be 1/3

Step-by-step explanation:

There are 6 faces in a dice and 2 of which are less than three. So the answer would 2/6 which is simplified as 1/3.

snow_tiger [21]3 years ago

4 0

Answer:

2/6 (33.33%)

Step-by-step explanation:

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Bill sees two boxes of baseball cards at a card show. The first box has 150 cards for $12.55.The second box has 120 cards for $9

Grace [21]

Answer: Cards in second box are cheaper.

Step-by-step explanation:

We are told that the first box has 150 cards for $12.55. Therefore, the cost of one card would be:

= $12.55 / 150

= $0.084.

The second box has 120 cards for $9.60. Therefore, the cost if one card would be:

= $9.60 / 120

= $0.08

Therefore, the cards in the second box are cheaper.

6 0

2 years ago

Please help me I don't knoe

forsale [732]

Answer:

x = sqrt(147)

Step-by-step explanation:

This is a right triangle, so we can use the Pythagorean theorem.

a^2 + b^2 = c^2 where a and b are the legs and c is the hypotenuse.

x^2 +7^2 = 14^2

x^2 +49 = 196

Subtract 49 from each side

x^2 = 147

Take the square root of each side

sqrt(x^2) = sqrt(147)

x = sqrt(147)

4 0

2 years ago

Read 2 more answers

In a school, there is a ratio of 4 boys to 5 girls. If there are a total of 450 students, how many girls are there? *

denpristay [2]

Answer: there are 200 girls in the school.

Step-by-step explanation:

In a school, there is a ratio of 4 boys to 5 girls. The total ratio would be the sum of the proportion of boys and the proportion of girls. Therefore,

Total ratio = 4 + 5 = 9

If there are a total of 450 students, it means that the number of girls in the school would be

Proportion of girls/ total ratio × total number of students. Therefore,

The number of girls is

5/9 × 450 = 200

7 0

3 years ago

Can someone help quick

9966 [12]

Step-by-step explanation:

22+2x+8= x+20

2x+30=x+20

x+30=20

x=-10

answer is -10

3 0

2 years ago

"Immediately after a ban on using hand-held cell phones while driving was implemented, compliance with the law was measured. A r

sergiy2304 [10]

Answer:

(a) Null Hypothesis, $H_0$ : $p_1-p_2=0$ or $p_1= p_2$

Alternate Hypothesis, $H_A$ : $p_1-p_2\neq 0$ or $p_1\neq p_2$

(b) We conclude that there is a statistical difference in these two proportions measured initially and then one year later.

Step-by-step explanation:

We are given that a random sample of 1,250 drivers found that 98.9% were in compliance. A year after the implementation, compliance was again measured to see if compliance was the same (or not) as previously measured.

A different random sample of 1,100 drivers found 96.9% compliance."

Let $p_1$ = proportion of drivers that were in compliance initially

$p_2$ = proportion of drivers that were in compliance one year later

(a) Null Hypothesis, $H_0$ : $p_1-p_2=0$ or $p_1= p_2$ {means that there is not any statistical difference in these two proportions measured initially and then one year later}

Alternate Hypothesis, $H_A$ : $p_1-p_2\neq 0$ or $p_1\neq p_2$ {means that there is a statistical difference in these two proportions measured initially and then one year later}

The test statistics that will be used here is Two-sample z proportion statistics;

T.S. = $\frac{(\hat p_1-\hat p_2)-(p_1-p_2)}{\sqrt{ \frac{\hat p_1(1-\hat p_1)}{n_1} + \frac{\hat p_2(1-\hat p_2)}{n_2}} }$ ~ N(0,1)

where, $\hat p_1$ = sample proportion of drivers in compliance initially = 98.9%

$\hat p_2$ = sample proportion of drivers in compliance one year later = 96.9%

$n_1$ = sample of drivers initially = 1,250

$n_2$ = sample of drivers one year later = 1,100

(b) So, the test statistics = $\frac{(0.989-0.969)-(0)}{\sqrt{ \frac{0.989(1-0.989)}{1,250} + \frac{0.969(1-0.969)}{1,100}} }$

= 3.33

Now, P-value of the test statistics is given by;

P-value = P(Z > 3.33) = 1 - P(Z $\leq$ 3.33)

= 1 - 0.99957 = 0.00043

Since in the question we are not given with the level of significance so we assume it to be 5%. Now at 5% significance level, the z table gives critical values between -1.96 and 1.96 for two-tailed test.

Since our test statistics does not lies within the range of critical values of z, so we have sufficient evidence to reject our null hypothesis as it will fall in the rejection region due to which we reject our null hypothesis.

Therefore, we conclude that there is a statistical difference in these two proportions measured initially and then one year later.

7 0

3 years ago