A translation is applied to the square formed by the points A(−3, −4) , B(−3, 5) , C(6, 5) , and D(6, −4) . The image is the squ
2 answers:
You might be interested in
Answer:
Gail will need 12 yards of white fur, 8 yards of blue striped and 2 yards of the pink felt.
Step-by-step explanation:
We are given that,
The amount of yards for making one costume of different fabrics are,
White fur fabric = =
yards
Blue striped fabric = 1 yard
Pink felt for ears = yards.
So, we have,
The amount required to make 8 costumes are,
White fur fabric = = 3×4 = 12 yards
Blue striped fabric = 1×8 = 8 yards
Pink felt for ears = = 2 yards.
Thus, Gail will need 12 yards of white fur, 8 yards of blue striped and 2 yards of the pink felt.
Answer:
Yes, this provide enough evidence to show a difference in the proportion of households that own a desktop.
Step-by-step explanation:
We are given that National data indicates that 35% of households own a desktop computer.
In a random sample of 570 households, 40% owned a desktop computer.
<em><u>Let p = population proportion of households who own a desktop computer</u></em>
SO, Null Hypothesis, : p = 25% {means that 35% of households own a desktop computer}
Alternate Hypothesis, : p
25% {means that % of households who own a desktop computer is different from 35%}
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 570 households who owned a desktop computer = 40%
n = sample of households = 570
So, <u><em>test statistics</em></u> =
= 2.437
<em>Since, in the question we are not given with the level of significance at which to test out hypothesis so we assume it to be 5%. Now at 5% significance level, the z table gives critical values of -1.96 and 1.96 for two-tailed test. Since our test statistics doesn't 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.</em>
Therefore, we conclude that % of households who own a desktop computer is different from 35%.