In_class_Practice2-solution

# In_class_Practice2-solution - In-class Practice 2...

This preview shows pages 1–3. Sign up to view the full content.

1 In-class Practice 2 NAME: _____________________________Solution______________________ BUAD 310 USC ID# :_________________________________________________________ LAB TIME ___________________________________________________ ARIF ANSARI PART 1 - MULTIPLE CHOICE [5 points each] 1. Based on the Normal Quantile plot, we can say , a) The Width is approximately uniformly distributed b) The Width is approximately normally distributed Å Answer c) The Width is Skewed to the right d) The Width is Skewed to the left Distributions Width 0 0.1 0.2 0.3 0.4 0.5 0.6 .01 .05 .10 .25 .50 .75 .90 .95 .99 -3 -2 -1 0 1 2 3 Normal Quantile Plot (based on histogram and Q-Q plot we can tell it is approximately normally distributed) 2. If the sampling population is normally distributed , then the distribution of the sample mean is ` a) Generally a skewed distribution b) Exactly normal distribution Å Answer c) Approximately normal distribution, if “n” is large d) Generally not a normal distribution e) None of the above (if population is normally distributed then x-bar is exactly normally distributed.) 3. Which of the following statements is not true? a) In the normal distribution, the total area under the curve is equal to one.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
2 b) In the normal distribution, the right half of the curve is a mirror image of the left half, since the distribution is symmetric. c) In any normal distribution, the mean, median, mode, and standard deviation are all at the same position on the horizontal axis. Å Answer d) In the normal distribution, the curve is asymptotic but never intercepts the horizontal axis either to the left or right. e) In the normal distribution, the total area beneath the curve represents the probability for all possible outcomes for a given event. (stdev is not a location.) 4. A sample size of “n”, n < 30 is drawn from a Non -Normal distribution with mean μ and standard deviation σ . By Central limit theorem, the distribution of the sample mean is a) Exactly normal with mean μ and variance σ 2 /n b) Non normal with mean μ and variance σ 2 /n Å Answer c) Approximately normal with mean μ and variance σ 2 /n d) Non normal with mean μ and variance σ 2 e) None of the above 5. A sample size of “n”, n 30 is drawn from a Non –Normal distribution with mean μ and standard deviation σ . By Central limit theorem, the distribution of the sample mean is a) Exactly normal with mean μ and variance σ 2 /n b) Non normal with mean μ and variance σ 2 /n c) Approximately normal with mean μ and variance σ 2 /n Å Answer d) Non normal with mean μ and variance σ 2 e) None of the above 6. A point estimate is defined as: a) The average of the sample values (this is an example for point estimate)
This is the end of the preview. Sign up to access the rest of the document.

## This note was uploaded on 06/29/2008 for the course BUAD 310 taught by Professor Lv during the Summer '07 term at USC.

### Page1 / 9

In_class_Practice2-solution - In-class Practice 2...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online