Is 10.5 rational or irrational number ?
2 answers:
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<em>The complete exercise with the answer options is as follows:</em>
Mancini's Pizzeria sells four types of pizza crust. Last week, the owner tracked the number sold of each type, and this is what he found.
Type of Crust Number Sold
Thin crust 364
Thick crust 240
Stuffed crust 176
Pan style 260
Based on this information, of the next 3000 pizzas he sells, how many should he expect to be thick crust? Round your answer to the nearest whole number. Do not round any intermediate calculations.
Answer:
692 thick crust pizzas
Step-by-step explanation:
With the data given in the exercise, we must first find the total number of pizzas, then we must find the proportion between the thick crust pizzas and the total number of pizzas, finally we must propose a rule of three to find the new proportion of crust pizzas thick on a total of 3000 pizzas.
Type of Crust Number Sold
Thin crust 364
Thick crust 240
Stuffed crust 176
Pan style 260
total pizzas : 1040
Now we must calculate for 3000 pizzas how much would be the total of thick crust pizzas.For that we must use the relationship found, that is, in 1040 pizzas there are 240 thick crust pizzas
1040→240
3000→x
x= = 692
Now we have a new proportion that out of 3000 pizzas there are a total of 692 thick crust pizzas
Answer:
No, we can't reject the dealer's claim with a significance level of 0.05.
Step-by-step explanation:
We are given that a local car dealer claims that 25% of all cars in San Francisco are blue.
You take a random sample of 600 cars in San Francisco and find that 141 are blue.
<u><em>Let p = proportion of all cars in San Francisco who are blue</em></u>
SO, Null Hypothesis, : p = 25% {means that 25% of all cars in San Francisco are blue}
Alternate Hypothesis, : p
25% {means that % of all cars in San Francisco who are blue is different from 25%}
The test statistics that will be used here is <u>One-sample z proportion</u> <u>statistics</u>;
T.S. = ~ N(0,1)
where, = sample proportion of 600 cars in San Francisco who are blue =
= 0.235
n = sample of cars = 600
So, <u><em>test statistics</em></u> =
= -0.866
<em>Now at 0.05 significance level, the z table gives critical values of -1.96 and 1.96 for two-tailed test. Since our test statistics lies within the range of critical values of z so we have insufficient evidence to reject our null hypothesis as it will not fall in the rejection region due to which we fail to reject our null hypothesis.</em>
Therefore, we conclude that 25% of all cars in San Francisco are blue which means the dealer's claim was correct.