Answer:
40
Step-by-step explanation:
there are 4 quarters so if one quarter is 10 then 4 quarters are 40
10 x 4 = 40
7) How many grams of calcium will Sean take in a week?
Answer:
Step-by-step explanation:
statment/reason
1) HK≅JK / given (S)
2) IK bisects ∠HKJ / given
3) ∠3≅∠4 / angle bisectors form congruent angles (A)
4) HK≅JK / given
5) IK ≅IK / reflexive propriety (S)
6) ΔIHK≅ΔIJK / SAS theorem of congruency
7) ∠1≅∠2 / corsponding parts of congruent Δs are ≅
8) IK bisects ∠HIJ / angle bisectors form congruent angles
Answer:
1= 29
2= 61
3= 90
4= 29
5= 90
Step-by-step explanation:
A rectangle has 4 - 90 degree angles. This means angles 3 and 5 are 90. This means the other angle will be split into two parts that add together to 90. If one is 61 then the other is 29. This is angle 4. This means angle 2 is 61 and angle 1 is 29 because rectangles have parallel sides.
Here, we are required to find the value of the other angles in the diagram attached to this answer sheet.
The value of the angles are;
The understanding of the triangle theorem and line theorems is very important to resolve this.
m∠1 + m∠2 = 180°(Theorem:sum of angles on a straight line =180⁰)
m∠1 + 98 = 180
m∠1 = 180 - 98
m∠2 + m∠3 + m∠7 = 180° (Theorem=sum ofangles in a triangle = 180⁰)
98 + 23 + m∠7 = 180
m∠7 + 121 = 180
m∠7 = 180 - 121
m∠4 = m∠7 (Theorem = alternate angles are equal)
m∠6 + m∠7 + m∠8 = 180° (Theorem = sum of angles on a straight line = 180)
m∠6 + 59 + 70 = 180
m∠6 + 129 = 180
m∠6 = 180 - 129
m∠4 + m∠8 + m∠9 = 180° (Theorem = sum of angles in a triangle = 180)
59 + 70 + m∠9 = 180
m∠9 + 129 = 180
m∠9 = 180 - 129
m∠4 + m∠5 = 180° (Theorem = sum of angles on a straight line = 180)
m∠5 + 59 = 180
m∠5 = 180 - 59
m∠10 + m∠9 = 180° (Theorem = sum of angles on a straight line = 180⁰)
m∠10 + 51 = 180
m∠10 = 180 - 51
Read more:
Answer:
The answer is below
Step-by-step explanation:
The complete question is given in the image attached below
m∠1 + m∠2 = 180° (sum of angles on a straight line)
m∠1 + 98 = 180
m∠1 = 180 - 98
m∠1 = 82°
m∠2 + m∠3 + m∠7 = 180° (sum of angles in a triangle)
98 + 23 + m∠7 = 180
m∠7 + 121 = 180
m∠7 = 180 - 121
m∠7 = 59°
m∠4 = m∠7 (alternate angles)
m∠4 = 59°
m∠6 + m∠7 + m∠8 = 180° (sum of angles on a straight line)
m∠6 + 59 + 70 = 180
m∠6 + 129 = 180
m∠6 = 180 - 129
m∠6 = 51°
m∠4 + m∠8 + m∠9 = 180° (sum of angles in a triangle)
59 + 70 + m∠9 = 180
m∠9 + 129 = 180
m∠9 = 180 - 129
m∠9 = 51°
m∠4 + m∠5 = 180° (sum of angles on a straight line)
m∠5 + 59 = 180
m∠5 = 180 - 59
m∠5 = 121°
m∠10 + m∠9 = 180° (sum of angles on a straight line)
m∠10 + 51 = 180
m∠10 = 180 - 51
m∠10 = 129°
Answer:
X + 1/2X + 1/5(1/2X) = 1,600,000
Step-by-step explanation:
Si se plantea que en una herencia de $1,600,000, la primer hermana recibirá un monto de dinero indeterminado, mientras que la segunda recibirá un medio del valor que reciba la primera, y la segunda recibirá un quinto de lo que reciba la segunda, la ecuación que visualiza dicha situación es la siguiente:
X + 1/2X + 1/5(1/2X) = 1,600,000
X + 1/2X + 1/10X = 1,600,000
10X + 5X + X = 16,000,000
16X = 16,000,000
X = 16,000,000 / 16
X = 1,000,000
Así, la primer hermana recibirá $1,000,000, la segunda $500,000, y la tercera $100,000.
a. If the sample variance is s^2=32 , are the data sufficient to conclude that the treatment has a significant effect using a two-tailed test with alpha=.05
b. If the sample variance is s^2=72 , are the data sufficient to conclude that the treatment has a significant effect using a two-tailed test with alpha=.05 ?
c. Comparing your answer for parts a and b, how does the variability of the scores in the sample influence the outcome of a hypothesis test?
A hypothesis test was conducted to evaluate the treatment's effect. For both variances, we failed to reject the null hypothesis, so we can't conclude that the treatment had a significant effect. The variability of scores plays a crucial role, as more variability makes it harder to identify a significant effect.
To determine if the treatment has a significant effect, we perform a hypothesis test using the sample mean (M), sample variance (s^2), and population mean (μ). The null hypothesis is that there's no effect from the treatment (μ=M), while the alternative hypothesis is that there is an effect (μ≠M).
a. For sample variance s^2=32, we can use the formula for the t score: t = (M - μ)/(s/√n) = (35 - 40)/(√32/√8) = -2.24. Based on a two-tailed t-distribution table, the critical t values for α=.05 and 7 degrees of freedom (n-1) are approximately -2.365 and 2.365. Our t value (-2.24) lies within this range, so we fail to reject the null hypothesis. We cannot conclude that the treatment has a significant effect.
b. Repeat the same process with sample variance s^2=72. The t value is now (35 - 40)/(√72/√8) = -1.48, again falling within the range of the critical t values. We can't conclude that the treatment has a significant effect.
c. As the variability (s^2) of the sample scores increases, it becomes more difficult to find a significant effect. Higher variability introduces more uncertainty, which can mask actual changes caused by the treatment.
#SPJ12
To evaluate the effect of a treatment using a two-tailed test with alpha = 0.05, we compare the calculated t-value to the critical t-value. The sample variance influences the outcome of the hypothesis test, with a larger variance leading to a wider critical region.
a. To test if the treatment has a significant effect, we will conduct a two-tailed hypothesis test using the t-distribution. The null hypothesis states that the treatment has no effect (μ = 40), while the alternative hypothesis states that the treatment has an effect (μ ≠ 40). With a sample size of 8, degrees of freedom (df) will be n-1 = 7. We will use the t-test formula to calculate the t-value, and compare it to the critical t-value from the t-table with α = 0.05/2 = 0.025. If the calculated t-value falls outside the critical region, we reject the null hypothesis and conclude that the treatment has a significant effect.
b. Similar to part a, we will conduct a two-tailed t-test using the same null and alternative hypotheses. With a sample size of 8, df = n-1 = 7. We will calculate the t-value using the sample mean, population mean, and sample variance. Comparing the calculated t-value to the critical t-value with α = 0.05/2 = 0.025, if the calculated t-value falls outside the critical region, we reject the null hypothesis and conclude that the treatment has a significant effect.
c. The variability of the scores in the sample, as indicated by the sample variance, influences the outcome of the hypothesis test. In both parts a and b, the sample variance is given. A larger sample variance (s^2 = 72 in part b) indicates more variability in the data, meaning the scores in the sample are more spread out. This leads to a larger t-value and a wider critical region. Therefore, it becomes easier to reject the null hypothesis and conclude that the treatment has a significant effect.
#SPJ11