1.According to survey data collected from 500 students in a recent Stat class, the histogram for the number of hours of sleep they typically got per night is close to the normal curve with an average of 6.3 hours and a SD of 1.4 hours.

a) Find percentage of students who sleep between 7 and 8 hours

b) A student who sleeps only 5 hours per night is at the _______th percentile of the score distribution

2.Consider the following set of ten numbers: 5, 5, 5, 7, 7, 7, 7, 3, 3, 1a) Find the average and the media of these numbers

c) Find the standard deviation

d) If you were to cut every number in the list in half (i) the new average would be
(ii) the new median would be
(iii) the new standard deviation would be

e) Now suppose you add the number 10 to the original list (so the new list has 11 numbers)
(i) the average would be

(ii) the median would be

1. Suppose you would like to do a survey of undergraduate students on your campus to find out how much time on the average they spend studying per week. You obtain from the registrar a list of all students currently enrolled and draw your sample from this list.

a. What is your sampling frame?

b. What is your target population?

c. Explain how you would draw a simple random sample for this study.

d. Assume that the registrar’s list also contains information about each student’s major. One could then select a stratified random sample, stratifying on major. What main benefit can result from using a stratified random sample instead of a simple random sample? Would you expect this benefit to be obtained by stratifying on major? Explain.

e. How might you obtain a cluster sample? When should you consider using this type of sampling design?

f. Which type of sampling design is most appropriate for this research problem? Explain.

Answer True or False

1. For graph representation, adjacency Matrix is more efficiency than adjacency list in term of searching for edge.

2. Topological sort runs in O(|V| + |E|) where |V| is the number of vertices, and |E| is the number of edges in the input graph.

3. If vertex u can reach vertex v, and vertex v can reach vertex u, then vertices u and v are in the same Strongly-connected component (SCC).

4. The Bellman-Ford algorithm will run forever if the input graph has negative weights on the edges.

5. For a graph with only positive edge weights, Dijkstra's algorithm solves the single-source shortest path (SSSP) problem faster than Bellman-Ford on a graph.

6. Dynamic programming depends on the input problem having an optimal substructure.

7. The longest-common subsequence problem on strings of length n and m can be solved in time O(nm).

8. The adjacency matrix’s space complexity is O(|V|+|E|), for a graph G = .

9. Given any two strings S1 and S2, there is only one longest common subsequence (that is, the LCS is unique).

10. Depth-First Search runs in O(|V| + |E|) where |V| is the number of vertices, and |E| is the number of edges in the input graph.

Breadth-First Search finds the shortest distance --- in terms of the number of hops --- from source vertex to each other reachable vertex in a graph.

Kruskal's algorithm is a greedy algorithm.

For any graph G with positive edge weights, there is only 1 minimum-spanning-tree (MST) for G.

The time complexity of rod-cutting problem is Θ(n2)

2^(n+1)= O(2^n)

Cruz Company uses LIFO for inventory costing and reports the following financial data. It also recomputed inventory and cost of goods sold using FIFO for comparison purposes. 2017 2016 LIFO inventory $ 190 $ 140 LIFO cost of goods sold 770 710 FIFO inventory 260 165 FIFO cost of goods sold 725 — Current assets (using LIFO) 250 220 Current liabilities 170 150 1. Compute its current ratio, inventory turnover, and days' sales in inventory for 2017 using (a) LIFO numbers and (b) FIFO numbers. (Round your answers to 1 decimal place.)

QS 16-7 Computing cash from asset sales LO P3

The following selected information is from Ellerby Company’s comparative balance sheets.

The income statement reports depreciation expense for the year of $26,500. Also, furniture costing $61,000 was sold for its book value on December 31, 2017.

Complete the general ledger accounts to calculate the cash received from the sale of furniture.
  

Compute cash flows from investing activities using the above company information. (Amounts to be deducted should be indicated by a minus sign.)
  

A comparative balance sheet and income statement is shown for Cruz, Inc.

Furniture costing $67,600 is sold at its book value in 2017. Acquisitions of furniture total $53,000 cash, on which no depreciation is necessary because it is acquired at year-end. What is the cash inflow related to the sale of furniture?
  

QS 16-9 Computing financing cash flows LO P3

The following selected information is from Princeton Company’s comparative balance sheets.

  
The company’s net income for the year ended December 31, 2017, was $54,000.

1. Complete the T-accounts to calculate the cash received from the sale of its common stock during 2017.
  

Question 1. My student union poll included another question regarding the preference for different dog breeds. I find that there is a statistically significant association between preferred dog breeds and gender of the students. I calculate a Cramer's V test and get a result of 0.05. What conclusion would I make about this result?

A) The Cramer's V score disproves our statistical significant finding.

B) The result was statistically significant, but not substantively significant.

C) The Cramer's V value further proves that the result is significant.

Question 2. I decide to conduct another poll outside the student union, and I want to ensure that my poll will have a low probability of Type II error and will be able to detect a difference with a medium effect size. I run the following code:

pwr.chisq.test(w = 0.3, N=NULL, df = 20, sig.level = 0.05, power = 0.8)

I get the following output in R:

Chi squared power calculation

w = 0.3
N = 232.8977
df = 20
sig.level = 0.05
power = 0.8

What does this output tell me about how I need to design my next poll.

A) I need a sample size of 233 students to obtain a result with the power I desire to have in my analysis.

B) Since I set my sample size at 233 I will achieve a power of 0.8.

C) A sample size of 230 should be sufficient for my poll.

D) My new poll needs a power of 0.8 to have an effect size of 0.3.

Question 3. Which of the following reflects the substantive significance of a statistic?

A) effect size

B) p-value

C) beta

D) alpha

Write a function that accepts a dictionary and produces a sorted list of tuples

The dictionary looks like this:

{‘US’: [{'Chicago, IL': ('2/1/2020 19:43', 2, 0, 0)}, {'San Benito, CA': ('2/3/2020 3:53', 2, 0, 0)}, {'Santa Clara, CA': ('2/3/2020 0:43', 2, 0, 0)}, {'Boston, MA': ('2/1/2020 19:43', 1, 0, 0)}, {'Los Angeles, CA': ('2/1/2020 19:53', 1, 0, 0)}, {'Orange, CA': ('2/1/2020 19:53', 1, 0, 0)}, {'Seattle, WA': ('2/1/2020 19:43', 1, 0, 0)}, {'Tempe, AZ': ('2/1/2020 19:43', 1, 0, 0)}], 'Australia' : [{'New South Wales': ('2/1/2020 18:12', 4, 0, 2)}, {'Victoria': ('2/1/2020 18:12', 4, 0, 0)}, {'Queensland': ('2/4/2020 16:53', 3, 0, 0)}, {'South Australia': ('2/2/2020 22:33', 2, 0, 0)}]

For these counts, I need to use the numbers that are bolded above). The returned sorted list (in descending order) will contain key-value pairs such that each key is a country and the corresponding value is the number of cases observed within that country.

For example: [('Australia', 13),(‘US’: 11)]

In a study of memory recall, ten students from a large statistics and data analysis class were
selected at random and given 15 minutes to memorize a list of 20 nonsense words. Each was
asked to list as many of the words as he or she could remember both 1 hour and 24 hours later.
The data are as shown in Table 1. Is there evidence to suggest the mean number of words recalled
after 1 hour exceeds the mean recall after 24 hours by more than 3? Use a significance level of
0.05.