CS609 Assignment 05 solution

S.No.	Question	Answer
1	Whether this entry represents an active partition? (3 marks)	No
2	What is the starting CHS address of the partition represented by this entry? Give answer in proper (C, H, S) format. (4 marks)	(1016, 161, 1)
3	What type of partition is represented by this entry? (3 marks)	FAT32
4	What is the ending CHS address of the partition represented by this entry? Give answer in proper (C, H, S) format. (4 marks)	(1023, 9, 63) Not confirm
5	What is the starting Sector of the partition represented by this entry? (3 marks)	63
6	What is the size of the partition represented by this entry? (in sectors) (3 marks)	20482812

CS610 GDB Solution Spring 2012

Do you think wireless networks will totally replace the wired or fixed networks in coming future? Prove validity of your opinion.

Idea Solution:
• Wired Local Area Networks make use of Ethernet cables and network adapters. Numerous computers can be wired to one another by using an Ethernet crossover cable. Wired LANs also need vital devices like hubs, switches, or routers to aid further computers.
• For dial-up connections to the Internet, the computer hosting the modem should administer Internet Connection Sharing or similar software to share the connection with every other computers on the network.
• Broadband routers permit easier sharing of cable modem or DSL Internet connections, furthermore they often include built-in firewall.
• Ethernet cables should proceed from each computer to a different computer or to the central device.
• The accurate cabling configuration for a wired LAN differs depending on the merge of devices, the form of Internet connection.
• Following hardware installation, the lasting steps in configuring either wired or wireless LANs do not contrast a great deal. Equally rely on standard Internet Protocol and network operating system configuration options.
Advantages and Disadvantages of Wired Networking
advantages:
• The equipment is inexpensive.
• Many computers have a wired network adapter.
• Wired networks transfer information more swiftly
• Wired networks are generally more secure than wireless networks
disadvantages:
• Running the wires from each room within the home can be a difficult task.
• Network cables can look disorganized.
• Network cables can disconnect or become faulty consequently causing the connection to fail.
• Adding more computers to a wired network may result in unexpected expense if you run out of connections on your network and could slow down the network.
All wired networks differ from each other. The most familiar type of wired network is an Ethernet network.


Wireless vs. Wired 
There are two kinds of network technologies:
• Wireless - communicates through radio waves
• Wired - communicates through data cables (most commonly Ethernet-based)

Why choose a wireless network?

Wireless networks don't use cables for connections, but rather they use radio waves, like cordless phones. The advantage of a wireless network is the mobility and freedom from the restriction of wires or a fixed connection. The benefits of having a wireless network include:
• Mobility and freedom - work anywhere
• No restriction of wires or a fixed connection
• Quick, effortless installation
• No cables to buy
• Save cabling time and hassle
• Easy to expand
Also known as Wi-Fi, or Wireless Fidelity, wireless networks allow you to use your network devices anywhere in an office or home, even out on the patio. You can check your e-mail or surf the Internet on your laptop anywhere in your house. There is no need to drill holes in the wall and install Ethernet cables. You can network anywhere - without wires. Outside your home, wireless networking is available in public "hotspots," such as coffee shops, businesses, hotel rooms, and airports. This is perfect for those of you who do a lot of traveling.

Why choose a wired network?

Wired networks have been around for decades. Wired networking technology found today is known as Ethernet. The data cables, known as Ethernet network cables or wired (CAT5) cables, connect computers and other devices that make up the networks. Wired networks are best when you need to move large amounts of data at high speeds, such as professional-quality multimedia. The benefits of having a wired network include:
• Relatively low cost
• Offers the highest performance possible
• Fast speed - standard Ethernet cable up to 100Mbps.
• Faster speed - Gigabit Ethernet cable up to 1000Mbps

WLAN vs LAN
LAN stands for Local Area Network, which is a collection of computers and other network devices in a certain location that are connected together by switches and/or routers that facilitate the communication of the network elements. Each computer or network element is connected to the switches/routers via a UTP cable. The added letter in WLAN stands for wireless. This is a type of network where the data is not transmitted via cables but over the air through the use of wireless transmitters and receivers.WLANs are deployed in areas where a wide number of computers may connect to the network but not at the same time. Places like coffee shops often add WLAN to their shops to entice more customers who do not stay for extended periods. Even at home where you have a somewhat fixed number of computers that connect to the network, WLAN is also preferred as it gives users the freedom to move around the house and carry their laptops with them without needing to fuss with cables. For areas where the computers are pretty much fixed, a wired LAN is very desirable due to the advantages that it offers.First off, a wired LAN is much faster compared to a WLAN. Most wireless routers nowadays are limited to a theoretical maximum speed of 54mbps while a contemporary wired LAN has a bandwidth of 100mbps. Gigabit network equipment can even ramp this up to 1000mbps or 1Gbps. This might not be such a big issue for browsing the internet or sending email but when you are copying large files, it can take a while with a WLAN.WLANs are also vulnerable to attack as just about anyone with a strong enough transceiver is able to detect the signal. Access can then be achieved by breaking the encryption used by the router through certain software. The information that is being transmitted through the WLAN can also be collected by malicious person and used in a variety, often destructive, ways. In order to intercept data in a wired LAN, you need to physically connect to a switch or a router.Summary:1. LAN refers to a wired network while WLAN is used to refer to a wireless network.2. LAN is commonly used in fixed networks while WLAN is common in areas where computers are moved quite often.3. WLAN is more convenient to users compared to LAN.4. LAN is much faster compared to WLAN.5. LAN is more secure compared to WLAN. 

CS302 Assignment No 5 Solution Spring 2012

Question 1                                                                                        Marks 10
Give next sequence of states for 5 bit Johnson counter having initial value as 00111 (you are required to give next 5 values) in tabular form as shown below,

Clock Pulse	Q0	Q1	Q2	Q3	Q4
…	…	…	…	…	…

Question 2                                                                                 Marks 10
Give next sequence of states for 5 bit Ring counter having initial value as 00100 (you are required to give next 5 values)

Clock Pulse

Q0

Q1

Q2

Q3

Q4

Solution:

CS601 Assignment No 4 Solution Spring 2012

Q. 1. Suppose a sender sent a word “assignment” for which the receiver received the following binary:
“01100001011010010111001101101001011001110110111001101110011001010110111001110100”
By applying the complete process of LRC using even parity, you are required to check that, is the same word received by the receiver or not? Also write the word received by the receiver.

Binary Code	Alphabet	Binary Code	Alphabet	Binary Code	Alphabet	Binary Code	Alphabet
0110 0001	a	0110 1000	h	0110 1111	o	0111 0110	v
0110 0010	b	0110 1001	i	0111 0000	p	0111 0111	w
0110 0011	c	0110 1010	j	0111 0001	q	0111 1000	x
0110 0100	d	0110 1011	k	0111 0010	r	0111 1001	y
0110 0101	e	0110 1100	l	0111 0011	s	111 1010	z
0110 0110	f	0110 1101	m	0111 0100	t
0110 0111	g	0110 1110	n	0111 0101	u

Table 1

HINT: First convert the word “assignment” into binary equivalent with the help of the given table 1. The LRC calculated by the sender is not appended with the given binary. It is also your task to calculate the LRC by yourself.

Q1 ….. Solution

Word sent
01100001    a
01110011    s
01110011    s
01101001    i
01100111    g
01101110    n
01101101    m
01100101    e
01101110    n
01110100    t
…………
00010011    LRC
………………………………………………
Word Received
01100001    a
01101001    i
01110011    s
01101001    i
01100111    g
01101110    n
01101110    n
01100101    e
01101110    n
01110100    t
…………
00001010    LRC
Word sent and word received is not same!

ENG101 Assignment No 4 Solution Spring 2012

Q1) ‘Paraphrasing is just another name for your writing style’. Paraphrase the following paragraphs in your own words. 
  
Solution:
One day the demon was in passive mood and has invented a glass and was happy to note that the greenery, good looking vegetation and the picture of human beings looks distorted and one cannot recognize their faces. The demon was happy of his cunning invention,
All who attends the demon’s school talked about the wonder of distorted glass, they carried thr glass everywhere till there wasn’t anybody who didn’t see the world and mankind thru this distorted glass.
They flew to heaven with this distorted glass to see the angel. At high altitude the glass became slippery and fell from their hands, landed on earch and broke in millions of pieces some are big some are as small as dust particle. When this small itom of glass stuck in the eye, the person looked the world thru this glass and found the distorted picture of mankind and the world. Spectacle was also made by this glass piece & the person could not see the right and just, they always see the distortion of images and truth.
The demon laughed at the wickedness and mischief that he has done by inventing the glass. Still there are particles are floating in the air by which the people always see the distorted side of the world.

Q.2   UNDERLINE the FIVE clichés from the given passage. (5)

Answer:

It is clear as crystal that after joining Hassan enterprises, Aleena became busy

 as a bee. She was mostly sick and tired due to over exertion. Her family members

 And friends were bored to tears even in her presence as she would indulge herself

 In her office work even at home. Her complexion also became pale. Before that,

 She used to be as red as a rose.

Q.3Fill in the blanks with the help of appropriate choices.

1-      Every trade and profession has its own …..

Technical jargon.

Formal jargon

simple jargon

complex jargon

2- All writing problems do not involve …..

 Grammar

 Syntax

semantics

pragmatics

 3-Careful writers avoid weakening their writing with …..

Slangs

Clichés

proverbs

idioms

 4-Punctuation depends upon …..

Grammar

Linguistics

stylistics

phonetics

 5-In essay writing, note making is a skill and it is a .….

Personal affair

Formal affair

informal affair

public affair

MTH202 Asignment # 4 Solution (Spring 2012)

Assignment 4 Of MTH202 (Spring 2012)

  

Question 1                                                                                                            Mark: 5

There are 8 men and 10 women members of a club. How many committees of seven persons can be formed, having 4 women?

Answer:

C(10,4).C(8,3)=11760

Question 2                                                                                                           Marks: 5

Compute ëxû and éxù for x = –3.01 

Answer:

ë-3.01û=-4

é-3.01ù=-3

Question 3                                                                                                           Marks: 5

(a) Determine whether the given graph has a Hamilton circuit? If  it does, find such a circuit, if it does not , given an argument to show why no such circuit exists.    (Marks=2)

Answer:

Yes this graph has Hamilton circuit and the circuit is abcdea

(b)  Give the degree of each vertex in the figure (given below)     (Marks=3)

   Answer:

Deg(A)=1,deg (B)=3,deg(C)=3,deg(D)=1

CS607 GDB Solution Spring July 2012

 SOLUTION::-
Machine learning has been central to AI research from the beginning. Unsupervised learning is the ability to find patterns in a stream of input. Supervised learning includes both classification and numerical regression. Classification is used to determine what category something belongs in, after seeing a number of examples of things from several categories. Regression is the attempt to produce a function that describes the relationship between inputs and outputs and predicts how the outputs should change as the inputs change. In reinforcement learning the agent is rewarded for good responses and punished for bad ones. These can be analyzed in terms of decision theory, using concepts like utility. The mathematical analysis of machine learning algorithms and their performance is a branch of theoretical computer science known as computational learning theory

MTH401 Assignment No 3 Solution Spring July 2012

MTH401 Assignment No 3 Solution Spring July 2012

Another Solution

MTH401Assignment3Solution -

CS401 Assignment # 5 Idea Solution Spring July 2012

 CS401 Assignment # 5 Idea Slution Spring July 2012

Q 1.

Solution:-

To learning assembly language it requires a considerable effort. It is quite evident that we have had neglected the vital role of the immense development in the technology of computer especially in the industrial and other technological fields. In these days it becomes possible for the designers to connect the personal computers with some outside apparatus by means of integrating suitable adapters which can be fixed in the expansion slot. It is one of the adequate methods know to be used in connection and communication. Assembly language which is needed to achieve the communication between the card and the processor inside computer using 74LS244 chips and line drivers with three states output to provide a unidirectional buffering for sixteen computer lines. This humble research paper is being undertaken to give a workable answer of some queries. It is found that the output of any generator used here is quite feasible to illustrate a different times by different stimulate. This study is short enough to include such advanced knowledge properly.

Finally, it is observed the assembly language reached at by this research is quickly of which is hoped to be utilized

Q2. How can communication be achieved between computer processor and adapter card? Which type of assembly instructions are used for this purpose, See the code which is displayed “ALLAH” in Arabic language.

Solution:
In these days it becomes possible for the designers to connect the personal computers with some outside apparatus by means of integrating suitable adapters which can be fixed in the expansion slot. It is one of the adequate methods know to be used in connection and communication. Assembly language which is needed to achieve the communication between the card and the processor inside computer using 74LS244 chips and line drivers with three states output to provide a unidirectional buffering for sixteen computer lines.
We can achieve communication between computer processor and adapter card by using assembly language instructions. We attached the hardware to the computer and write the desire output containing programs by using given BIOS services in assembly language.
 These are assembly instructions in the given program.
MOV, use to move data from one register to another
OUT, for the output
DEC, decrement data
INC, increment data
JUZ, different types of jumps etc
JN

MTH302 GDB Solution Spring 2012

 MTH302 GDB Solution Spring 2012

CONSTRUCT A BUSINESS PROBLEM WHICH SHOWS A POSITIVE RELATIONSHIP BETWEEN INDEPENDENT AND DEPENDENT VARIABLES USING REGRESSION ANALYSIS

Solution:
Marketing research professionals often use inferential or descriptive statistics to guide major marketing decisions. There are a number of statistical tests that explore the relationship between the independent variable(s) and the dependent variable. The key is to translate the business problem into a statistical problem, solve the problem statistically, then translate the statistical solution into an actionable business solution.

Dependent Variable

The dependent variable — also called the response variable — is the output of a process or statistical analysis. Its name comes from the fact that it depends on or responds to other variables. Typically, the dependent variable is the result you want to achieve. In marketing, the results desired are tied to sales revenue. Sales as a dependent variable can be looked at in many ways, such as sales of a specific doll, sales of a category like toy cars, overall sales at a particular store, or even sales for the entire company.

Independent Variable

An independent variable is an input to a process or analysis that influences the dependent variable. While there can only be one dependent variable in a study, there may be multiple independent variables. When the dependent variable is sales revenue, the elements of the marketing mix — product, price, promotion and place — will definitely influence the dependent variable and can therefore be identified as independent variables.

Regression Analysis in Marketing

Marketing research employs a statistical tool called regression analysis to measure the strength of the relationship between the dependent variable and the independent variables. For example, a frozen yogurt shop could set loyalty card discounts, base price, and time of day as the independent variables to test not only the direct effect each factor has on parfait sales, but whether there is interaction between the variables. If, when the base price is low, loyalty card discounts influence sales less than when the base price is high, there is an interaction between the two factors.

Choosing the Right Variables

Asking the right question will lead you to the right answer. The more specific you can make your dependent variable — for instance, sales of a single MP3 player model as opposed to sales of all electronics — the better chance you have of isolating the independent variables that truly influence it. Also, even when you know your goal, you look at it a variety of different ways. For instance, “At what price can we make $100,000 per quarter in sales of product A?” is a subtly different question than, “At a price of $10, how many people will buy product A per quarter?” Look in the Resources section for further reading on how to start with the right question and use the right methodology to answer it.

A variable is an event, idea, value or some other object or category that a researcher or business can measure. Variables can be dependent or independent. Dependent variables vary by the factors that influence them, but independent variables stand on their own — changes in other variables have no effect on them. An independent variable in one context may be a dependent variable in another. An independent variable in business may affect sales, expenses and overall profitabilityIndependent variables that affect sales include customer demographics, store location and weather. Customer demographics include age, occupation, family status, income level and gender. These factors affect what a customer needs, which affects sales and ultimately profits. A store located in a densely populated metropolitan area may have higher sales than a store in a sparsely populated rural area. Similarly, customers may go shopping when the weather is pleasant, but few would venture outside in stormy or snowy weather. Some variables have a circular relationship with sales. For example, sales depend on advertising, but the level of advertising expenses also depends on sales.

Expenses

The prices of raw materials, labor wage rates and facility rental rates are independent expense variables. The prices of raw materials, such as food commodities, metals and minerals, do not change, regardless of how much a small business spends on them. Labor wage rates and facility rental rates are other examples of independent expense variables. They affect the cost structure of a small business, but the owner cannot change market wage rates or rental rates by himself.

Economy

Economic variables affect business profitability. The income of individual customers and profits of business customers are independent economic variables that affect overall business performance. During a recession, customers earn and spend less, which leads to declining business sales. Conversely, during a period of economic growth, customers earn and spend more, which increases business sales and profits. The interest rate on a bank loan or line of credit is an independent variable because it affects expenses and profits. However, the borrowing needs of a small business do not change interest rates.

Considerations: Dependent Variables

In the business context, profit is a dependent variable because it depends on the economy, sales and expenses. Product quality depends on the manufacturing and design processes. The number of employees laid off during a recession depends partly on declining business revenues. Government tax revenue depends on customer income, business profits, capital gains and other variables.

Solution # 2:- 

Regression Basics For Business Analysis If you've ever wondered how two or more things relate to each other, or if you've ever had your boss ask you to create a forecast or analyze relationships between variables, then learning regression would be worth your time. In this article, you'll learn the basics of simple linear regression - a tool commonly used in forecasting and financial analysis. We will begin by learning the core principles of regression, first learning about covariance and correlation, and then move on to building and interpreting a regression output. A lot of software such as Microsoft Excel can do all the regression calculations and outputs for you, but it is still important to learn the underlying mechanics. Variables At the center of regression is the relationship between two variables, called the dependent and independent variables. For instance, suppose you want to forecast sales for your company and you've concluded that your company's sales go up and down depending on changes in GDP. The sales you are forecasting would be the dependent variable because their value "depends" on the value of GDP, and the GDP would be the independent variable. You would then need to determine the strength of the relationship between these two variables in order to forecast sales. If GDP increases/decreases by 1%, how much will your sales increase or decrease? Covariance The formula to calculate the relationship between two variables is called covariance. This calculation shows you the direction of the relationship as well as its relative strength. If one variable increases and the other variable tends to also increase, the covariance would be positive. If one variable goes up and the other tends to go down, then the covariance would be negative. The actual number you get from calculating this can be hard to interpret because it isn't standardized. A covariance of five, for instance, can be interpreted as a positive relationship, but the strength of the relationship can only be said to be stronger than if the number was four or weaker than if the number was six. Correlation Coefficient We need to standardize the covariance in order to allow us to better interpret and use it in forecasting, and the result is the correlation calculation. The correlation calculation simply takes the covariance and divides it by the product of the standard deviation of the two variables. This will bound the correlation between a value of -1 and +1. A correlation of +1 can be interpreted to suggest that both variables move perfectly positively with each other, and a -1 implies they are perfectly negatively correlated. In our previous example, if the correlation is +1 and the GDP increases by 1%, then sales would increase by 1%. If the correlation is -1, a 1% increase in GDP would result in a 1% decrease in sales - the exact opposite. (Correlation is also a well-known metric to diversify an investor's portfolio; see Diversification: Protecting Portfolios From Mass Destruction to learn more.) Regression Equation Now that we know how the relative relationship between the two variables is calculated, we can develop a regression equation to forecast or predict the variable we desire. Below is the formula for a simple linear regression. The "y" is the value we are trying to forecast, the "b" is the slope of the regression, the "x" is the value of our independent value, and the "a" represents the y-intercept. The regression equation simply describes the relationship between the dependent variable (y) and the independent variable (x). Free Trading Guide - GFT y=bx+a The intercept, or "a", is the value of y (dependent variable) if the value of x (independent variable) is zero. So if there was no change in GDP, your company would still make some sales - this value, when the change in GDP is zero, is the intercept. Take a look at the graph below to see a graphical depiction of a regression equation. In this graph, there are only five data points represented by the five dots on the graph. Linear regression attempts to estimate a line that best fits the data, and the equation of that line results in the regression equation. Figure 1: Line of best fit Source: Investopedia, 2009. Excel Now that you understand some of the background that goes into regression analysis, let's do a simple example using Excel's regression tools. We'll build on the previous example of trying to forecast next years sales based on changes in GDP. The next table lists some artificial data points, but these numbers can be easily accessible in real life. Year Sales GDP 2005 100 1.00% 2006 250 1.90% 2007 275 2.40% 2008 200 2.60% 2009 300 2.90% Just eyeballing the table, you can see that there is going to be a positive correlation between sales and GDP. Both tend to go up together. Using Excel, all you have to do is click the Tools drop-down menu, select Data Analysis, and from there choose Regression. The popup box is easy to fill in from there; your Input Y Range is your "Sales" column and your Input X Range is the change in GDP column; choose the output range for where you want the data to show up on your spreadsheet and press OK. You should see something similar to what is given in the table below (I've left out parts of the output that isn't relevant for this article). (See Microsoft Excel Features For The Financially Literate for some tips on how to efficiently use Excel) Regression Statistics Coefficients Multiple R 0.8292243 Intercept 34.58409 R Square 0.687613 GDP 88.15552 Adjusted R Square 0.583484 - - Standard Error 51.021807 - - Observations 5 - - Interpretation The major outputs you need to be concerned about for simple linear regression are the R-squared, the intercept and the GDP coefficient. The R-squared number in this example is 68.7% - this shows how well our model predicts or forecasts the future sales. Next we have an intercept of 34.58, which tells us that if the change in GDP was forecasted to be zero, our sales would be about 35 units. And lastly, the GDP correlation coefficient of 88.15 tells us that if GDP increases by 1%, sales will likely go up by about 88 units. So how would you use this simple model in your business? Well if your research leads you to believe that the next GDP change will be a certain percentage, you can plug that percentage into the model and generate a sales forecast. This can help you develop a more objective plan and budget for the upcoming year. Of course this is just a simple regression and there are models that you can build that use several independent variables called multiple linear regressions. But multiple linear regressions are more complicated and have several issues that would need another article to discuss.Regression Basics For Business Analysis If you've ever wondered how two or more things relate to each other, or if you've ever had your boss ask you to create a forecast or analyze relationships between variables, then learning regression would be worth your time. In this article, you'll learn the basics of simple linear regression - a tool commonly used in forecasting and financial analysis. We will begin by learning the core principles of regression, first learning about covariance and correlation, and then move on to building and interpreting a regression output. A lot of software such as Microsoft Excel can do all the regression calculations and outputs for you, but it is still important to learn the underlying mechanics. Variables At the center of regression is the relationship between two variables, called the dependent and independent variables. For instance, suppose you want to forecast sales for your company and you've concluded that your company's sales go up and down depending on changes in GDP. The sales you are forecasting would be the dependent variable because their value "depends" on the value of GDP, and the GDP would be the independent variable. You would then need to determine the strength of the relationship between these two variables in order to forecast sales. If GDP increases/decreases by 1%, how much will your sales increase or decrease? Covariance The formula to calculate the relationship between two variables is called covariance. This calculation shows you the direction of the relationship as well as its relative strength. If one variable increases and the other variable tends to also increase, the covariance would be positive. If one variable goes up and the other tends to go down, then the covariance would be negative. The actual number you get from calculating this can be hard to interpret because it isn't standardized. A covariance of five, for instance, can be interpreted as a positive relationship, but the strength of the relationship can only be said to be stronger than if the number was four or weaker than if the number was six. Correlation Coefficient We need to standardize the covariance in order to allow us to better interpret and use it in forecasting, and the result is the correlation calculation. The correlation calculation simply takes the covariance and divides it by the product of the standard deviation of the two variables. This will bound the correlation between a value of -1 and +1. A correlation of +1 can be interpreted to suggest that both variables move perfectly positively with each other, and a -1 implies they are perfectly negatively correlated. In our previous example, if the correlation is +1 and the GDP increases by 1%, then sales would increase by 1%. If the correlation is -1, a 1% increase in GDP would result in a 1% decrease in sales - the exact opposite. (Correlation is also a well-known metric to diversify an investor's portfolio; see Diversification: Protecting Portfolios From Mass Destruction to learn more.) Regression Equation Now that we know how the relative relationship between the two variables is calculated, we can develop a regression equation to forecast or predict the variable we desire. Below is the formula for a simple linear regression. The "y" is the value we are trying to forecast, the "b" is the slope of the regression, the "x" is the value of our independent value, and the "a" represents the y-intercept. The regression equation simply describes the relationship between the dependent variable (y) and the independent variable (x). Free Trading Guide - GFT y=bx+a The intercept, or "a", is the value of y (dependent variable) if the value of x (independent variable) is zero. So if there was no change in GDP, your company would still make some sales - this value, when the change in GDP is zero, is the intercept. Take a look at the graph below to see a graphical depiction of a regression equation. In this graph, there are only five data points represented by the five dots on the graph. Linear regression attempts to estimate a line that best fits the data, and the equation of that line results in the regression equation. Figure 1: Line of best fit Source: Investopedia, 2009. Excel Now that you understand some of the background that goes into regression analysis, let's do a simple example using Excel's regression tools. We'll build on the previous example of trying to forecast next years sales based on changes in GDP. The next table lists some artificial data points, but these numbers can be easily accessible in real life. Year Sales GDP 2005 100 1.00% 2006 250 1.90% 2007 275 2.40% 2008 200 2.60% 2009 300 2.90% Just eyeballing the table, you can see that there is going to be a positive correlation between sales and GDP. Both tend to go up together. Using Excel, all you have to do is click the Tools drop-down menu, select Data Analysis, and from there choose Regression. The popup box is easy to fill in from there; your Input Y Range is your "Sales" column and your Input X Range is the change in GDP column; choose the output range for where you want the data to show up on your spreadsheet and press OK. You should see something similar to what is given in the table below (I've left out parts of the output that isn't relevant for this article). (See Microsoft Excel Features For The Financially Literate for some tips on how to efficiently use Excel) Regression Statistics Coefficients Multiple R 0.8292243 Intercept 34.58409 R Square 0.687613 GDP 88.15552 Adjusted R Square 0.583484 - - Standard Error 51.021807 - - Observations 5 - - Interpretation The major outputs you need to be concerned about for simple linear regression are the R-squared, the intercept and the GDP coefficient. The R-squared number in this example is 68.7% - this shows how well our model predicts or forecasts the future sales. Next we have an intercept of 34.58, which tells us that if the change in GDP was forecasted to be zero, our sales would be about 35 units. And lastly, the GDP correlation coefficient of 88.15 tells us that if GDP increases by 1%, sales will likely go up by about 88 units. So how would you use this simple model in your business? Well if your research leads you to believe that the next GDP change will be a certain percentage, you can plug that percentage into the model and generate a sales forecast. This can help you develop a more objective plan and budget for the upcoming year. Of course this is just a simple regression and there are models that you can build that use several independent variables called multiple linear regressions. But multiple linear regressions are more complicated and have several issues that would need another article to discuss.