Answer:
d) The difference exists due to chance since the test statistic is small
Step-by-step explanation:
From the given information:
Population mean = 178 cm
the sample mean = 177.5 cm
the standard deviation = 2
the sample size = 25
The null hypothesis and the alternative hypothesis can be computed as:
Null hypothesis:
Alternative hypothesis:
The t-test statistics is determined by using the formula:
Degree of freedom df = n- 1
Degree of freedom df = 25 - 1
Degree of freedom df = 24
At the level of significance ∝ = 0.05, the critical value = 2.064
Decision rule: To reject the null hypothesis if the test statistics is greater than the critical value at 0.05 level of significance
Conclusion: We fail to reject the null hypothesis since the test statistics is lesser than the critical value and we conclude that the difference exists due to chance since the test statistic is small
First you add like terms in which this case is -.46x and .16x which equals -.3x then divide 6.6 into -.3 which is -22. x = -22
Answer:
y=-4/13x-28/13
Step-by-step explanation:
m=y2-y1/x2-x1
m=-4-0/6-(-7)
m=-4-0/6+7
m=-4/13
y-y1=m(x-x1)
y-0=-4/13(x-(-7))
y-0=-4/13x-28/13
y=-4/13x-28/13
Answer:
i believe the answer is C
Step-by-step explanation:
i dont know its just what i would choose im not the smartests in math
"1 indicating a coupon and all other outcomes indicating no coupon"
Probability is (number of successful outcomes) / (number of possible outcomes)
Theoretical Probability of rolling a 1: 1/8
Experimental Probability of using coupons: 4/48 = 1/12
So, the experimental probability of a customer using a coupon (that is, 1/12) is smaller than the theoretical probability of rolling a 1 (that is, 1/8).