A travel agent (TA) in Athens named “Thomas o Mageiras” has contracts with 135
hotels from all categories (stars) in the three major Greek summer destinations,
namely Crete, Ionian Islands and South Aegean Islands. In order to better support its
clients the TA yearly collects and updates data regarding the performance of these
hotels.
The dataset in the table that follows, provides various measures of
all 135 hotels, summarized in the following variables:
Variables Description
STARS Hotel class category
Total_Rooms Total number of rooms per hotel

Region_ID

1= Crete
2=Southern Aegean Islands
3=Ionian Islands

ARR_MAY Average Room Rate in May (in €)
ARR_AUG Average Room Rate in August (in €)
L_COST Labor cost per hotel (in €)
Note: The empty cells in the given Excel spreadsheet indicate missing values.

Question 1:
1.1 Construct the frequency distribution, the percentage distribution and the frequency
histogram of the variables ARR_MAY and ARR_AUG for ALL 135 hotels. Use
the same class width = 25 for both frequency distributions. Comment on the
characteristics of the distributions.
1.2 Construct separately, the frequency distributions and the percentage distributions
of the variable ARR_AUG for each of the three destinations. Use the same class
width = 35 for each of the three frequency distributions.
1.3 Construct separately, the frequency distributions and the percentage distributions
of the variable ARR_MAY for hotels with a) Number of rooms ≤ 50 considered
as small size hotels b) Number of rooms > 50 considered as large size hotels. Use
the same class width = 25 for both frequency distributions.

1.4 Plot three histograms of the frequency distributions of the variable ARR_AUG,
one for each of the three destinations, and comment on the main characteristics of
the three distributions.
1.5 Plot two histograms of frequency distributions of the variable ARR_MAY, one
for the small and one for the large size hotels, and comment on the main
characteristics of the two distributions.
1.6 What conclusions can you reach concerning the differences in distribution a) of
ARR_AUG among the three destinations and b) of ARR_MAY between the
small and the large size hotels?

2008 Summer Olympics in Beijing, China, in a world record of 9.58 seconds. That works out to be about 23.4 miles per hour over the course of the race. For a brief period during that sprint, Bolt reached an astounding 40 feet per second (27.51 mph). As a physical activity, running is very different from walking. In running, a person's legs flex and the muscles stretch and then contract during acceleration. As the runner's muscles release and absorb energy, the overall energy in the person's body changes and leads to increased speed. What Makes An Elite Runner? Scholars believe that the fastest runners — the elite sprinters like Bolt - are those who use a low amount of energy for every foot that they run, compared to other people. The ability to do that is influenced by a number of different factors, including their age, sex and distribution of muscles. The fastest of the elite runners are young men. The way in which a person's body moves in time and space is called biomechanics. The possible speed of a runner is influenced by their biomechanics, especially how their legs move as they run. Many different factors could influence a person's running speed, including how much time the foot spends touching the ground, how far the legs swing and the angle and distance of the stride. In particular, sprint runners maximize their acceleration and top speed by applying more force relative to their body weight. Their ankles move faster and they take more steps per minute. Long-Distance Runners: When considering speed, sports researchers also look at long-distance runners, who race distances between 3 and 26 miles. The fastest of these runners use considerable plantar pressure, which is the amount of pressure the foot puts on the ground. Changes in biomechanical factors, or how the legs move over time and space, also seem to have a significant effect. As with sprinters, the fastest group in marathon running is men aged between 25 and 29. Those men have an average speed between 558 and 577 feet per minute. This information was gathered from the marathons that were run in Chicago and New York between 2012 and 2016. The New York City marathon runs in waves. There are four groups of runners who begin the race roughly 30 minutes apart. As a result, statistics are available for runner speeds at 3-mile segments throughout the race. Researcher Zhenquan Lin and his team used that data to show that one factor of speed is competition. Runners increase speed and change positions more frequently at the end of the race. The Upper Limits In comparison to other animals, humans are very slow. The fastest animal on record is the cheetah, which can run up to 70 mph. Even Usain Bolt can only attain a fraction of that. Recent research on the most elite runners has led sports medicine expert Peter Weyand and his team to suggest that the upper limit might reach 35-40 mph. So far though, no one has been willing to confirm that in an official publication. In other words, scientists still need to find more Proof. Statistics: According to Rankings.com, the fastest three male sprinters in the world today are Usain Bolt, Tyson and Asafa Powell. Bolt and Powell are Jamaican, and tyson is American. Bolt set the 100-meter record at the 2008 Summer Olympic Games in Beijing, China, completing the race in 9.58 seconds. His speed was 34.25 feet per second. tyson's fastest time is 9.69 seconds. Powell's is 9.72 seconds. The fastest three female sprinters are Florence Griffith Joyner, Carmelita Jeter and Marion Jones, who are all American. Joyner's fastest time in the 100-meter was 10.49 seconds, set in the 1988 Olympics in Seoul, South Korea, at a speed of 31.27 feet per second. Jeter's fastest time is 10.64 seconds. Jones' is 10.65 seconds. The three fastest male marathon runners are, according to Runners World, Dennis Kimetto of Kenya, Kenenisa Bekele of Ethiopia and Eliud Kipchoge of Kenya. Kimetto set the record for the fastest marathon time at the Berlin Marathon in 2014. He completed the 26.2-mile race in just 2 hours, 2 minutes and 57 seconds. Bekele finished the Berlin Marathon in 2:03:03 in 2016. Kipchoge ran the London Marathon in 2:03:05 in 2016. The three fastest female marathon runners are Paula Radcliffe of England, Mary Keitany of Kenya and Tirunesh Dibaba of Kenya. Radcliffe completed the 2003 London Marathon in 2:15:25. Keitany completed the 2017 London Marathon at 2:17:01. Dibaba finished the same race in 2:17:56.

Examine the ideas in the article. in a short paragraph that explains the central idea of the article. Use at least two details from the article to support your response.

Raymond Santana created Computer Solutions on October 1, 2019. The company has been successful, and its list of customers has grown.

In response to requests from customers, R. Santana will begin selling computer software. The company will extend credit terms of 1/10, n/30, FOB shipping point, to all customers who purchase this merchandise. However, no cash discount is available on consulting fees. Also, Business Solutions does not use reversing entries and, therefore, all revenue and expense accounts have zero beginning balances as of January 1, 2020. Its transactions for January through March follow:

I am mainly interested in COGS and inventory transactions (journal entries), and both of the account end balances. Please show the work. Thank you

Develop and pseudocode for the code below:

#include <algorithm>
#include <iostream>
#include <time.h>

#include "CSVparser.hpp"

using namespace std;

//============================================================================
// Global definitions visible to all methods and classes
//============================================================================

// forward declarations
double strToDouble(string str, char ch);

// define a structure to hold bid information
struct Bid {
string bidId; // unique identifier
string title;
string fund;
double amount;
Bid() {
amount = 0.0;
}
};

//============================================================================
// Static methods used for testing
//============================================================================

/**
* Display the bid information to the console (std::out)
*
* @param bid struct containing the bid info
*/
void displayBid(Bid bid) {
cout << bid.bidId << ": " << bid.title << " | " << bid.amount << " | "
<< bid.fund << endl;
return;
}

/**
* Prompt user for bid information using console (std::in)
*
* @return Bid struct containing the bid info
*/
Bid getBid() {
Bid bid;

cout << "Enter Id: ";
cin.ignore();
getline(cin, bid.bidId);

cout << "Enter title: ";
getline(cin, bid.title);

cout << "Enter fund: ";
cin >> bid.fund;

cout << "Enter amount: ";
cin.ignore();
string strAmount;
getline(cin, strAmount);
bid.amount = strToDouble(strAmount, '$');

return bid;
}

/**
* Load a CSV file containing bids into a container
*
* @param csvPath the path to the CSV file to load
* @return a container holding all the bids read
*/
vector<Bid> loadBids(string csvPath) {
cout << "Loading CSV file " << csvPath << endl;

// Define a vector data structure to hold a collection of bids.
vector<Bid> bids;

// initialize the CSV Parser using the given path
csv::Parser file = csv::Parser(csvPath);

try {
// loop to read rows of a CSV file
for (int i = 0; i < file.rowCount(); i++) {

// Create a data structure and add to the collection of bids
Bid bid;
bid.bidId = file[i][1];
bid.title = file[i][0];
bid.fund = file[i][8];
bid.amount = strToDouble(file[i][4], '$');

//cout << "Item: " << bid.title << ", Fund: " << bid.fund << ", Amount: " << bid.amount << endl;

// push this bid to the end
bids.push_back(bid);
}
} catch (csv::Error &e) {
std::cerr << e.what() << std::endl;
}
return bids;
}

// FIXME (2a): Implement the quick sort logic over bid.title

/**
* Partition the vector of bids into two parts, low and high
*
* @param bids Address of the vector<Bid> instance to be partitioned
* @param begin Beginning index to partition
* @param end Ending index to partition
*/
int partition(vector<Bid>& bids, int begin, int end) {

int l = begin;
int h = end;

int pivot = (begin + (end - begin) / 2);
bool finished = false;

// this while loops continually increments the low point as long as it's below the pivot
// then continually decrements the high point as long as it's above the pivot
while(!finished) {

while(bids[l].title.compare(bids[pivot].title) < 0) {
++l;
}

while(bids[pivot].title.compare(bids[h].title) < 0) {
--h;
}

if (l >= h) {
finished = true;
// if variable l is not greater than or equal to h the two bids are swapped
} else {
swap(bids[l] , bids[h]);

//bring end points closer to one another

++l;
--h;
}
}
return h;
}

/**
* Perform a quick sort on bid title
* Average performance: O(n log(n))
* Worst case performance O(n^2))
*
* @param bids address of the vector<Bid> instance to be sorted
* @param begin the beginning index to sort on
* @param end the ending index to sort on
*/
void quickSort(vector<Bid>& bids, int begin, int end) {
}

// FIXME (1a): Implement the selection sort logic over bid.title

/**
* Perform a selection sort on bid title
* Average performance: O(n^2))
* Worst case performance O(n^2))
*
* @param bid address of the vector<Bid>
* instance to be sorted
*/
void selectionSort(vector<Bid>& bids) {
// this creates an index to the smallest minimum bid found
unsigned int smallest;
unsigned int largest = bids.size();

// place designates the position at which bids are sorted/unsorted
for (unsigned place = 0; place < largest; ++place) {
smallest = place;

for (unsigned j = place + 1; j < largest; ++j) {
if (bids[j].title.compare(bids[smallest].title) < 0) {
smallest = j;
}
}

if (smallest != place)
swap(bids[place], bids[smallest]);
}

}

/**
* Simple C function to convert a string to a double
* after stripping out unwanted char
*
* credit: http://stackoverflow.com/a/24875936
*
* @param ch The character to strip out
*/
double strToDouble(string str, char ch) {
str.erase(remove(str.begin(), str.end(), ch), str.end());
return atof(str.c_str());
}

/**
* The one and only main() method
*/
int main(int argc, char* argv[]) {

// process command line arguments
string csvPath;
switch (argc) {
case 2:
csvPath = argv[1];
break;
default:
csvPath = "eBid_Monthly_Sales_Dec_2016.csv";
}

// Define a vector to hold all the bids
vector<Bid> bids;

// Define a timer variable
clock_t ticks;

int choice = 0;
while (choice != 9) {
cout << "Menu:" << endl;
cout << " 1. Load Bids" << endl;
cout << " 2. Display All Bids" << endl;
cout << " 3. Selection Sort All Bids" << endl;
cout << " 4. Quick Sort All Bids" << endl;
cout << " 9. Exit" << endl;
cout << "Enter choice: ";
cin >> choice;

switch (choice) {

case 1:
// Initialize a timer variable before loading bids
ticks = clock();

// Complete the method call to load the bids
bids = loadBids(csvPath);

cout << bids.size() << " bids read" << endl;

// Calculate elapsed time and display result
ticks = clock() - ticks; // current clock ticks minus starting clock ticks
cout << "time: " << ticks << " clock ticks" << endl;
cout << "time: " << ticks * 1.0 / CLOCKS_PER_SEC << " seconds" << endl;

break;

case 2:
// Loop and display the bids read
for (int i = 0; i < bids.size(); ++i) {
displayBid(bids[i]);
}
cout << endl;

break;

// FIXME (1b): Invoke the selection sort and report timing results
    ticks = clock();

// call selectionSort method to sort the loaded bids
selectionSort(bids);

cout << bids.size() << " bids read" << endl;

// Calculate elapsed time and display result
ticks = clock() - ticks; // current clock ticks minus starting clock ticks
cout << "time: " << ticks << " clock ticks" << endl;
cout << "time: " << ticks * 1.0 / CLOCKS_PER_SEC << " seconds" << endl;

break;

// FIXME (2b): Invoke the quick sort and report timing results

   ticks = clock();

// call quickSort method to sort the loaded bids
quickSort(bids, 0, bids.size() - 1);

cout << bids.size() << " bids read" << endl;

// Calculate elapsed time and display result
ticks = clock() - ticks; // current clock ticks minus starting clock ticks
cout << "time: " << ticks << " clock ticks" << endl;
cout << "time: " << ticks * 1.0 / CLOCKS_PER_SEC << " seconds" << endl;

break;

}

cout << "Good bye." << endl;

return 0;
}

Which of the following statements about value is FALSE?

2.Relevance is a critical criterion in formulating a value claim for a positioning statement. The makers of Cialis, an erectile dysfunction (ED) drug, are considering a value claim that it "enhances intimacy and relationship." To assess the relevance of this claim, Cialis must determine if the claim:

3.Assume that Park Paper Products believes its customers typically use satisficing decision making when purchasing paper products. Which of the following would likely be the least effective market strategy?

4.All of the following should be part of Best Buy's in-store marketing strategy to influence sales of consumer electronics in its stores EXCEPT:

5.

Line is the most widely used messaging app in Japan, Thailand, and Taiwan. After achieving success by focusing on chatting, video calling, photo sharing, and other communication functions, the firm leveraged its large customer base to expand beyond these functions. Line now offers online purchasing, delivery, taxi-hailing, and financial services.
of the three major product policy decisions faced by a firm, Line has been primarily engaged in:

6.In the case study about the marketing of Propecia, who were the two key decision-makers involved in the purchase and use of Propecia?

7.You are the vice president of marketing for a regional chain of fine dining restaurants. You have created policies to ensure that every fulltime employee has the training and skills to deliver the highest quality customer experiences. For example, every server is authorized to surprise customers with one-bite appetizers as part of the company's Customer Delight program. The company refers to these policies as employee empowerment. This is an example that best matches which of the four sets of activities for creating a customer-centric culture?

3-bPrepare a journal entry to close any balance in the Manufacturing Overhead account to Cost of Goods Sold.

Record the entry to close any balance in the Manufacturing Overhead account to Cost of Goods Sold.\

4-

Matt’s Landscaping Pty Ltd is registered for GST purposes. It accounts for GST on the accruals basis and submits its Business Activity Statements monthly. Assume that all amounts in the question include GST when applicable.

The business operates from Brisbane’s north-side and its main business is to design and establish new gardens at shopping centres and office parks, and to provide ongoing garden maintenance services to clients.

During October 2018, Matt’s Landscaping Pty Ltd was involved in the following transactions:

* Designing and establishing a new garden at the refurbished Westfield shopping centre at North Lakes. The invoice issued on 25 October 2018 totalled $27,600.

* Ongoing garden maintenance services for clients. Invoices issued in October 2018 totalled $55,200.

* Matt’s Landscaping Pty Ltd prepared plans for the elaborate gardens of a new hotel being built in Dubai in the United Arab Emirates. The plans were sent to Dubai by airfreight on 1 October 2018. Matt’s Landscaping Pty Ltd issued an invoice for $17,500 on 15 October 2018.

* Purchases of plants, fertiliser and decorative stones from Brunnings Warehouse, one of Australia’s largest household hardware chains, totalled $9,900.

* The company purchased 100 square meters of Buffalo lawn from a retired school teacher who decided to dig up the lawn of his acreage in Caboolture to put down asphalt so that he no longer had to mow his lawn. The school teacher charged Matt’s Landscaping Pty Ltd $660 on 19 October 2018.

*The company purchased a second-hand lawnmower from a large supplier in Perth for $990 on 1 October 2018. The lawnmower was delivered a day later by a nationwide courier company that charged $110 for this service.

* Salaries and wages paid to staff in October 2018 totalled $12,000.

* Fuel costs for the company’s vehicles, lawnmowers and hedge trimmers totalled $1,980 during October 2018.

* The business operated from rented offices in North Lakes owned by a listed property group. Rent for October 2018 totalled $1,000.

* The October invoice that Matt’s Landscaping Pty Ltd received from the electricity and gas supplier for the rental property totalled $275.

* Purchases of milk, sugar, tea bags and coffee powder from a grocery store totalled $100 in October 2018. These were placed in a tea room in the rented offices for the exclusive use of staff.

* On 1 October 2018, Matt’s Landscaping Pty Ltd purchased a new one and a half tonne utility vehicle for $82,500.

* The company purchased specialised pruning shears from a company in France during October 2018. The shears cost $1,500 and international freight and insurance cost $100.

* Interest paid to the Commonwealth Bank of Australia in October 2018 on an overdraft facility totalled $660.

You are required to:

Calculate the GST payable or GST refundable for October 2018. Show all your calculations and provide reasons for your answers

The town of Malvern engages in the following transactions during its fiscal year ending September 30, 2021. All dollar amounts are in thousands. Prepare summary journal entries in its governmental funds. Base entries on generally accepted accounting principles now in effect.

(1)   At the beginning of the fiscal year 2021, the town levied property taxes of $180,000. It estimated that $6,000 will be uncollectible.

(2)   During fiscal year 2021, the town collected $150,000 prior to September 30, 2021.

(3)   The town collected $4,000 each month in October and November 2021, prior to preparing its 2021 financial statements. It expected to receive $4,000 each month for the next four months.

(4)   During the remainder of fiscal year 2022, the town collected $16,000 in tax relating to 2021, $140,000 related to 2022, and $10,000 applicable to 2023.

(5)   On November 20, 2021, it received $42,000 from the state for sales taxes collected on its behalf. The payment was for sales made in September that merchants were required to remit to the state by October 15.

(6)   In April, the town was awarded a state training grant of $500 for the period June 1, 2021, through May 31, 2022. In fiscal 2021, the town received the entire $500 but spent only $400.

(7)   The town requires each vendor who sells at its farmers' market to obtain an annual permit. The funds generated by the sale of these permits are used to maintain the market. The permits, which cover the period from June 1 through May 31, are not refundable. During fiscal year 2021, the town issued $66 worth in permits. It expects to collect an additional $12 within 60 days of the close of the fiscal year.

(8)   On May 1, 2021, a developer (in exchange for exemptions to zoning restrictions) donated several acres of land that the town intended to convert to a park. The land had cost the developer $100,000. At the time of the contribution, its fair market value was $280,000.

(9)   Several years earlier the town received a donation of a parcel of land, upon which it expected to build. During fiscal 2021, it opted to sell the land for $185. When acquired by the town, the land had a market value of $119.

At the beginning of the fiscal year 2021, The town of Marlvern acquired six police cars at a total cost of $200,000. The vehicles are expected to have a useful life of four years. Prepare the journal entries that the town would make in its governmental funds in the fiscal year based on the following scenarios:

(10)It paid for the cars in cash at the time of acquisition.

(11)It issued $200,000 in installment notes to the car dealer, agreeing to repay them in four annual payments of $63,095 at the end of each fiscal year (effective interest rate is 10%), starting in the year of acquisition.

The weights (in pounds) and ages (in months) of 35 randomly selected male bears in Yellowstone Park were recorded in a file male_bears.csv. A researcher runs the following code in R to read in the data.

> bears <- read.table(file="male_bears.csv", header=T, sep=",")

The researcher then runs the following code in R to fit a simple linear regression model oftheformyi =α+βxi +εi, i=1,2...n.Notethatsomevaluesintheoutputhave been removed.

> result <- lm(WEIGHT ~ AGE, data=bears) > summary(result)

Call:
lm(formula = WEIGHT ~ AGE, data Residuals:

Min 1Q Median 3Q -204.96 -45.82 -11.69 22.78

Coefficients:
Estimate Std. Error

(Intercept) 73.6415 19.3023
AGE 3.2052 0.3695
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘’1

Residual standard error: 75.13 on 33 degrees of freedom Multiple R-squared: 0.6952, Adjusted R-squared: 0.6859
F-statistic: 75.25 on 1 and 33 DF, p-value: **REMOVED**

1. i) Identify the response and predictor variables in the output above. [2]

2. ii) Using values from the output, write out the estimated linear regression equation.

   [2]

= bears)

Max 174.33

t value 3.815 8.675

Pr(>|t|) 0.000567 *** **REMOVED**

‘*’ 0.05 ‘.’ 0.1

2

3. iii) Provide an interpretation of the coefficient of the variable AGE in the output. [1]

4. iv) Write out the hypotheses being tested by the t-statistic circled in the output.

   [1]

5. v) What are your conclusions about the hypotheses in (iv)? Use statistical tables to arrive at your conclusion. [3]

The researcher then produced the following analysis for variance for the regression model.

> anova(result)
Analysis of Variance Table

Response: WEIGHT
          Df Sum Sq Mean Sq F value    Pr(>F)

AGE 1 424736 424736 75.251 5.017e-10 *** Residuals 33 186260 5644

6. vi) Using values from the analysis of variance output, compute the coefficient of determination for the regression model. [2]

7. vii) Provide an interpretation of the coefficient of determination. [1]

Some summary statistics for the variable AGE are provided below. > summary(bears$AGE)

Min. 1st Qu. Median Mean 3rd Qu. Max. 8.00 16.50 32.00 39.34 53.00 177.00

8. viii) Is the estimated regression equation in (ii) suitable for predicting the weight of a male bear who is 100 months old? Give a reason for your answer. If your answer was yes, find the predicted weight of a 100-month old male bear. [3]

9. ix) Is the estimated regression equation in (ii) suitable for predicting the weight of a female bear who is 100 months old? Give a reason for your answer. [2]

The researcher then produced the following diagnostic plots in R.

> qqnorm(result$residuals)
> qqline(result$residuals)

3

> plot(result$fitted, result$residuals)

10. x) For each of the plots above, explain the specific purpose of the plot. [2]

11. xi) State your conclusions made from observing each plot. [2]