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Meet Authors Jeff Slater and Sharon Wittry
Learn more about our Business Math offerings straight from the authors! Jeff Slater and Sharon Wittry are here to support you and are available to guide you through your course challenges. Take a glimpse into Math for Business and Finance and Practical Business Math Procedures and reach out to the authors with your questions and feedback.
Math For Business And Finance: An Algebraic Approach
Practical Business Math Procedures
14th edition, connect for business math features, smartbook 2.0.
Comprehensive Test Bank
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Connect for Business Math
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Giulio De Rensis
Year 12 maths b assignment. exponential data and reasoning
Wong King Teck
2019, International Journal of Financial Research
Consumer demand conditions for fluctuating roasted coffee and ineffective production planning often lead to excessive production. Excess production will lead to wasteful costs and maintenance of quality on roasted coffee. Production demand forecasting is the basis for making production demand decisions. The purpose of this study is to predict the number of production requests for the next period and determine the most suitable forecasting method in determining the amount of roasted coffee production demand. The object of the data taken is roasted coffee. Analysis methods use moving averages, weighted moving averages, and exponential smoothing. In determining the most suitable forecasting method based on the Mean Absolute Deviation (MAD) forecasting value and the smallest Mean Squared Error (MSE) of each method used. The results of this study indicate that the most suitable forecasting method is using a Weighted Moving Average with a three-month period and forecasting roasted coffee ...
The principle of least squares, innovated by the French mathematician Legendre, when applied to observed data in order to fit a mathematical curve yields normal equations. The parameters involved in the curve are estimated by solving the normal equations. The number of normal equations becomes larger when the number of parameters associated to the curve becomes larger. In this situation, the solution of the normal equations for estimating the parameters becomes more complicated. For this reason, one more convenient method has been search for computing the estimates of the parameters. The method has been developed by the stepwise application of the principle of least squares. The method innovated here consists of the elimination of parameters first and then the minimization of the sum of squares of the errors. In this paper, the method has been described with reference to the estimation of parameters of a linear curve based on observed data on monthly average minimum temperature at Guwahati
In exercises requiring estimations or approximations, your answers may vary slightly from the answers given here. 1. (a) The point (−1, −2) is on the graph of f , so f (−1) = −2. (b) When x = 2, y is about 2.8, so f (2) ≈ 2.8. (c) f (x) = 2 is equivalent to y = 2. When y = 2, we have x = −3 and x = 1. (d) Reasonable estimates for x when y = 0 are x = −2.5 and x = 0.3. (e) The domain of f consists of all x-values on the graph of f. For this function, the domain is −3 ≤ x ≤ 3, or [−3, 3]. The range of f consists of all y-values on the graph of f. For this function, the range is −2 ≤ y ≤ 3, or [−2, 3]. (f) As x increases from −1 to 3, y increases from −2 to 3. Thus, f is increasing on the interval [−1, 3]. 3. From Figure 1 in the text, the lowest point occurs at about (t, a) = (12, −85). The highest point occurs at about (17, 115). Thus, the range of the vertical ground acceleration is −85 ≤ a ≤ 115. Written in interval notation, we get [−85, 115]. 5. No, the curve is not the graph of a function because a vertical line intersects the curve more than once. Hence, the curve fails the Vertical Line Test. 7. Yes, the curve is the graph of a function because it passes the Vertical Line Test. The domain is [−3, 2] and the range is [−3, −2) ∪ [−1, 3]. 9. The person's weight increased to about 160 pounds at age 20 and stayed fairly steady for 10 years. The person's weight dropped to about 120 pounds for the next 5 years, then increased rapidly to about 170 pounds. The next 30 years saw a gradual increase to 190 pounds. Possible reasons for the drop in weight at 30 years of age: diet, exercise, health problems. 11. The water will cool down almost to freezing as the ice melts. Then, when the ice has melted, the water will slowly warm up to room temperature. 13. Of course, this graph depends strongly on the geographical location! 15. As the price increases, the amount sold decreases.
Dr. VARALAXMI T SHEDOLE
2018, Energy Procedia
This comprehensive technical note explains linear regression. It is indended for students with no prior knowlede of the topic. It is devided into nine sections, which may be assigned separately: 1. The simple linear model, 2. Fitting the model using least squares, 3. Important properties of the least-squares regression line, 4. Summary regression statistics, 5. Assumptions behind the linear model, 6. Model-building philosopy, 7. Forecasting using the linear model, 8. Using dummy variables to represent categorical variables, and 9. Useful data transformations. The sections correspond to stand-alone notes also available through Darden Business Publishing.
Rita Ceppitelli , Sri Winggowati
The simple differential equation y′ = ky, k ∈ IR is an important mathematical model. It is well known in Population Dynamics as the Malthusian Equation and it is familiar to food technologists as Bigelow’s First Law, which describes the microbial mortality at constant lethal temperatures. In the paper we focus on the process of thermal sterilization of milk. The Malthusian Equation is also a mathematical model for Newton’s law of cooling or heating. The rate of heat loss of a cooling body is proportional to the difference in temperatures between the body and its surroundings. In the paper we analyze the data of an experimental study on the cooling of coffee conduced by "Mathematics & Real Life" Project. The measurements of the temperature were taken using a centesimal temperature sensor connected to a computer for automatic data capture. Another simple differential equation is Darcy’s equation, a fundamental mathematical model in the filtration t heory. In the paper we are...
2016, Mathematical theory and modeling
The field of forecasting is concerned with approaches to determining what the future holds. It is also concerned with the proper presentation and use of forecasts. Fluctuations in the prices of commodities are a phenomenon that is of statistical significance. In modern mathematical and social sciences it is important that the field of forecasting is developed and designed as a tool to help decision making and planning. This project discusses how we can use simple objective methods of forecasting on price data to forecast to a relatively high degree of accuracy, the prices of commodities. The study highlighted on the adequacy of the quadratic method of curve fitting for forecasting the prices of local rice based on a 5-year data set. It shows that, though most models can predict the prices reasonably, by considering the R 2 values and the Root Mean Squared residual values, the quadratic models are better than the other models such as linear, lognormal, logistics and the simple expon...
Felicia Z Zhang
Environment, Development and Sustainability
1984, Journal of the American Statistical Association
Shewale Tanmay , Devesh Deochake
The following technical paper presents two case studies pertaining to Linear Regression analysis. Case study 1 presents the use regression analysis in the form of simple regression and multiple regression and elaborates the practical use of regression analysis in the decision making process of which predictor variables should be used in the analysis. Case study 2 presents the use of linear regression techniques in studying the September Sea Ice extent in the Arctic Ocean from year 1979 – 2012. This case study also shows the use of quadratic regression to represent the data with a continuously variable slopes in the regression equation.
1989, Computers & Industrial Engineering
2007, Journal of Statistical Planning and Inference
2019, Asia Proceedings of Social Sciences
The purpose of this investigation is to examine the variation of temperature in Afghanistan over the past 114 years. The historical dataset of the monthly average temperature from 1901 to 2015 were analyzed. The relationship between temperature and time during the four time intervals, i.e. (1901 -1930), (1931-1960), (1961-1990) and (1991-2015) is presented using a new analytical model based on the last –square method of estimation. We accurately fit a polynomial regression trend of degree 4 to the time series to describe the temperature variation. The results show the average difference of temperature between 2015 and 1901 increases about 1.03 °C. The average monthly difference between the maximum and minimum temperature was approximately 3.66 °C and the average monthly difference between the maximum and minimum temperature during these periods is approximately about 1.31 °C. This approach of modeling temperature using regression form significantly simplifies the data analysis. The ...
2017, SSRN Electronic Journal
2017, Energy Procedia
Journal of Statistics Education
Ashis kumar mukherjee
Journal of Physics: Conference Series
kai yang ng
Business Mathematics MAT112
Welcome to the MAT112 BUsiness Mathematics Courseweb. I hope you enjoy it!
Course learning outcomes.
At the end of the course, students should be able to:
Express basic algebraic concepts in solving business application problems. ( C2 )
Solve mathematical problems encountered in banking and finance, trading and retailing, and accounting. ( C3 )
Determine mathematical concepts to solve mathematical problems in banking and finance, trading and retailing, and accounting. ( C4 )
Relate business mathematics applications to their respective field. ( A4 )
The course is primarily designed to develop the mathematical knowledge needed by the students to meet the demands of business operation. It is to provide a solid coverage of the most basic and frequently occurring business situations.
Fundamental Concepts of Mathematics 1.1 Review on Algebra: 1.2 Sequence
Mathematical Applications in Banking and Finance 2.1 Simple Interest 2.2 Bank Discount and Promissory Notes 2.3 Compound Interest 2.4 Annuity
Mathematical Applications In trading and retailing 3.1 Trade and cash discounts 3.2 Mark up and Mark Down 3.3 Instalment Purchase
Mathematical Applications In Accounting 4.1 Depreciation
Proposed % marks approved by kpp.
40.00% Assignment - 4% out of 100 on Week 13. Passing Mark(s): 4 Individual Assignment CLO: 4
Quiz - 2% out of 100 on Week 3. Passing Mark(s): 2 Quiz 1 CLO: 1
Quiz - 2% out of 100 on Week 7. Passing Mark(s): 2 Quiz 2 CLO: 2
Quiz - 2% out of 100 on Week 11. Passing Mark(s): 2 Quiz 3 CLO: 3
Test - 15% out of 100 on Week 9. Passing Mark(s): 15 Test 1 CLO: 2
Test - 15% out of 100 on Week 14. Passing Mark(s): 15 Test 2 CLO: 3
60.00% Final Examination - 60% out of 100 on End of Semester. Passing Mark(s): 30 Final Examination (All Chapters) CLO: 1, 2, 3 Duration : 180 minutes
Demonstrate maturity of thoughts when responding to multiple inputs and contexts.
- Lau Too Kya,Phang Yook Ngor and Wee Kok Kiang, Business Mathematics for UiTM, 5th edition, Oxford Fajar Sdn Bhd, 2015, ISBN: n/a
- Paul Lau Ngee Kiong, Business Mathematics, 1st, UiTM Press, 2013, ISBN: n/a
- Gary Clendenen,Stanley A. Salzman, Business Mathematics, 13th, Pearson College Division, 2014, ISBN: n/a
- James Deitz,James Southam, Contemporary Business Mathematics for Colleges, 16th, Cengage Learning, 2012, ISBN: n/a
- Eugene Don, Joel Lerner, Schaum’s Outline of Basic Mathematics, 2nd, McGraw-Hill, 2009, ISBN: n/a
- Zin Ibrahim, Daud Mohamad, Business Mathematics, 1st, McGraw-Hill, 2008, ISBN: n/a
- Robert Brechner, and George Bergeman,, Contemporary Mathematics for Business and Contemporary Mathematics for Business and Consumers, 7th edition, Cengage Learning, 2015, ISBN: n/a
This module does not have other references
Past Test Paper With Answers Test 2 Dec 2019 Test 1 Nov 2019
Workshops Questions With Answers Nov 2019 Session 1 Answers
Nov 2019 Session 2 Answers
Text and figures are licensed under Creative Commons Attribution CC BY 4.0 . The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".
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MAT112 Business Mathematics Assignment Sample UiTM Malaysia
This is a business mathematics assignment from MAT112 at the university. The task involves solving simple mathematical problems that arise in the processing industry, such as production and inventory management for companies with limited resources like small businesses or large corporations alike.
The first section of the assignment is on linear equations and how to solve them. The questions begin with basic algebra, such as solving for x in the equation 3x + 5 = 10.
The next step is to move on to solving more complex linear equations with two or more variables. These types of equations are often seen in production or inventory management, where businesses need to find the optimal values for different variables to minimize cost or maximize profit.
The final section of the assignment deals with graphing linear equations and using them to solve problems. This is often used in business to visualize data and relationships between different variables. For example, a company might want to graph their sales data over time to identify trends. Once the trend is identified, the company can then make decisions about pricing, production, or marketing based on this information.
This business mathematics assignment is a great way to learn about solving equations and graphing linear equations. These are skills that are useful in many different aspects of the business. By solving the problems in this assignment, you will be better prepared to tackle real-world business challenges.
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Assignment Task 1: Understand basic algebra concepts in solving business application problems.
Algebra is the mathematics of equations and variables. It can be used to solve problems in various business applications such as pricing, inventory, and financial analysis.
One of the most basic algebra concepts is solving equations. An equation is a mathematical statement that states that two things are equal. For example, the equation 2 + 3 = 5 states that 2 + 3 is equal to 5. To solve an equation means to find the value of the variable that makes the equation true. In this example, the value of x (the variable) would be 5 since it makes 2 + 3 = 5 true.
Another basic algebra concept is solving systems of linear equations. A system of linear equations in two or more equations with the same variables. For example, the system of linear equations below has two equations and two variables (x and y):
equation 1: 2x + 3y = 11
equation 2: 4x – 5y = -1
Solving a system of linear equations means finding the values of the variables that make all the equations true. In this example, the values of x and y would be 2 and 1 respectively since they make both equations true.
Assignment Task 2: Solving mathematical problems in banking and finance, trading and retailing, and accounting.
There are a variety of ways to solve mathematical problems in banking and finance, trading and retailing, and accounting.
One way is to develop numerical methods that can be used to approximate solutions to specific problems.
Another way is to create models that approximate real-world situations mathematically, allowing for predictive analysis and making better decisions.
Additionally , business organizations commonly use software applications designed specifically for solving mathematical problems in their industry vertical. Typically, these software programs offer a wide range of features and functionality to users, including the ability to visualize data sets, run what-if scenarios, optimize equations or models, and output results in a variety of formats (e.g., reports, charts/graphs).
Ultimately, the most important thing is to choose the right approach for the specific problem at hand and to have a deep understanding of the underlying mathematics. With that said, there are several ways to solve mathematical problems in banking and finance, trading and retailing, and accounting – it just depends on what works best for you and the particular situation you’re facing.
Assignment Task 3: Apply mathematical concepts to solve mathematical problems in banking and finance, trading and retailing, and accounting.
Mathematical concepts can be used to solve a variety of banking, financial, trading and accounting problems. For example, basic algebra can be used to solve interest problems, geometry can be used to calculate discounts and profits, and calculus can be employed to value options contracts.
In addition, mathematical models can be created to help with risk assessment and fraud detection. Bankers and other finance professionals use these models to make informed decisions about where to invest money and how best to protect their assets. Trading professionals rely on mathematical models to help them identify profitable investment opportunities, while accountants use them to ensure that companies are accurately reporting their financial information.
Mathematics is a powerful tool that can be used to solve a wide range of problems in the business world. By harnessing the power of mathematics, bankers, financiers, traders and accountants can make more informed decisions, and ultimately help businesses to run more smoothly and profitably.
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Business Mathematics includes math courses taken on an undergraduate level by business individuals. These courses typically do not enter in the same depth because standard courses from the mathematics or research fields. The two most common mathematics courses consumed this form usually are Business Calculus and Business Statistics.
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