1.328 b. 2.539 c. 1.325 d. 2.528 ANSWER: a -go to the t-dtistrubution and use α=0.20 or confidence of 80% and use dof=19 3. Read the t statistic from the table of t distributions and circle the correct answer. A one-tailed test (upper tail), a sample size of 18 at a .05 level of significance t = a. 2.12 b.
Answer: False Difficulty: Medium 5. The sampling distribution of a sample statistic is the probability distribution of the population of all possible values of the sample statistic. Answer: True Difficulty: Easy 6. A sample statistic is an unbiased point estimate of a population parameter if the mean of the populations of all possible values of the sample statistic equals the population parameter. Answer: True Difficulty: Medium 7.
5. A test statistic is a value determined from sample information used to reject or not reject the null hypothesis. 6. The region or area of rejection defines the location of all those values that are so large or so small that the probability of their occurrence under a true null hypothesis is rather remote. 7.
Define Skewness Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean. The Skewness value can be positive or negative, or even undefined. 18. What is Standard deviation (STDEV) The standard deviation (SD) (represented by the Greek letter sigma, σ) shows how much variation from the average exists. Deviation (statistics) is the difference between the value of an observation and the mean of the population in mathematics and statistics.
Chapter 11 Comparisons Involving Proportions Learning Objectives 1. Be able to develop interval estimates and conduct hypothesis tests about the difference between the proportions of two populations. 2. Know the properties of the sampling distribution of the difference between two proportions[pic]. 3.
I first start with 0.00 less than the probability which is 0.20 then we start at 0.21 less than 0.53. I came up with 0.53 from adding the initial probability of 0.20 and the second 0.33. Next I start at 0.54 less than 0.90 these figures come from adding 0.53 plus the third probability of 0.37. Lastly, I start at 0.91 less than 1 and again I adding 0.90 plus the last probability of 0.10. Now let’s find the Average materials cost per unit.
1. A random sample of size 15 is selected from a normal population. The population standard deviation is unknown. Assume the null hypothesis indicates a two-tailed test and the researcher decided to use the 0.10 significance level. For what values of t will the null hypothesis not be rejected?
Are there asset classes that should be excluded or others that should be included? 9. Why might standard deviation NOT capture the risks of all asset classes? 10. Using the data from attachments 10-11 (provided below), compute the optimal portfolio allocations if the portfolio mean return objective is 6.4% with some constraints (all weights sum to 100%, weights on cash >= -50% and weights on all other asset classes >=0) and the investor wishes to minimize standard deviation.
TOPIC 8 Chi-Square goodness-of-fit test Problem 12.1 Use a chi-square goodness-of-fit to determine whether the observed frequencies are distributed the same as the expected frequencies (α = .05) Category | fo | fe | 1 | 53 | 68 | 2 | 37 | 42 | 3 | 32 | 33 | 4 | 28 | 22 | 5 | 18 | 10 | 6 | 15 | 8 | Step 1 Ho: The observed frequencies are distributed the same as the expected frequencies Ha: The observed frequencies are not distributed the same as the expected frequencies Step 2 df = k – m – 1 Step 3 α = 0.05 x 2 0.05, 5df = 11.0705 Step 4 Reject Ho if x 2 > 11.0705 Category | fo | fe | | 1 | 53 | 68 | | 2 | 37 | 42 | | 3 | 32 | 33 | | 4 | 28 | 22 | | 5 | 18 | 10 | | 6 | 15 | 8
The threshold is the deprivation cut-offs which are collected in the dimensional vector . If household achievement in a given indicator falls short of the respective cutoff , the household is said to be deprived in that indicator, that is if . From the achievement matrix and vector a deprivation matrix is obtained such that whenever and ,otherwise for all and for all . The vector summarizes the deprivation status values of household in all indicators across the human development dimensions and vector summarizes the deprivation status values of all households in indicator . The uncensored headcount ratio is calculated for indicator j as , which represents the percentage of households n deprived in indicator j. Deprivation in each of the d indicators observed may not