- published: 25 Feb 2015
- views: 51386
Projection, projector, or projective may refer to:
In economics, demand is the utility for a good or service of an economic agent, relative to his/her income. (Note: This distinguishes "demand" from "quantity demanded", where demand is a listing or graphing of quantity demanded at each possible price. In contrast to demand, quantity demanded is the exact quantity demanded at a certain price. Changing the actual price will change the quantity demanded, but it will not change the demand, because demand is a listing of quantities that would be bought at various prices, not just the actual price.)
Demand is a buyer's willingness and ability to pay a price for a specific quantity of a good or service. Demand refers to how much (quantity) of a product or service is desired by buyers at various prices. The quantity demanded is the amount of a product people are willing or able to buy at a certain price; the relationship between price and quantity demanded is known as the demand. (see also supply and demand). The term demand signifies the ability or the willingness to buy a particular commodity at a given point of time, ceteris paribus. Utility preferences and choices underlying demand can be represented as functions of cost, benefit, odds and other variables.
Demand forecasting is the art and science of forecasting customer demand to drive holistic execution of such demand by corporate supply chain and business management. Demand forecasting involves techniques including both informal methods, such as educated guesses, and quantitative methods, such as the use of historical sales data and statistical techniques or current data from test markets. Demand forecasting may be used in production planning, inventory management, and at times in assessing future capacity requirements, or in making decisions on whether to enter a new market
Demand forecasting is predicting future demand for the product. In other words it refers to the prediction of probable demand for a product or a service on the basis of the past events and prevailing trends in the present.
Forecasting demand based on expert opinion. Some of the types in this method are,
In statistics, linear regression is an approach for modeling the relationship between a scalar dependent variable y and one or more explanatory variables (or independent variables) denoted X. The case of one explanatory variable is called simple linear regression. For more than one explanatory variable, the process is called multiple linear regression. (This term should be distinguished from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable.)
In linear regression, the relationships are modeled using linear predictor functions whose unknown model parameters are estimated from the data. Such models are called linear models. Most commonly, the conditional mean of y given the value of X is assumed to be an affine function of X; less commonly, the median or some other quantile of the conditional distribution of y given X is expressed as a linear function of X. Like all forms of regression analysis, linear regression focuses on the conditional probability distribution of y given X, rather than on the joint probability distribution of y and X, which is the domain of multivariate analysis.
A time series is a sequence of data points that
1) Consists of successive measurements made over a time interval
2) The time interval is continuous
3) The distance in this time interval between any two consecutive data point is the same
4) Each time unit in the time interval has at most one data point
Examples of time series are ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average.
Non-Examples: The height measurements of a group of people where each height is recorded over a period of time and each person has only one record in the data set.
Panel data set is sometimes difficult to be differentiated from time series data set. One data set may exhibit both characteristics of panel data set and time series data set. One way to differentiate is to ask: what makes one data record unique from the other records? If the answer is the time data field, then this is a time series data set candidate. If determining a unique records requires a time data field and an additional identifier which is unrelated to time (student ID, stock symbol, country code), then it is a panel data candidate. If the differentiation lies on the non time identifier, then the data set is a cross sectional data set candidate.
Demand Forecasting | Techniques of Demand Forecasting
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Dark tranquillity - The fatalist (video projection)
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Projection of electrical energy Demand and Supply in Banten province
Managerial Economics; Management; Demand Forecasting | Techniques of Demand Forecasting; Introduction 00:00:00- 00:00:40 Demand Forecast 00:00:41- 00:02:15 *What is meant by demand forecasting? *The importance of demand forecast How to Forecast Demand? 00:02:16- 00:23:16 *Various steps for demand forecasting *Techniques of demand forecasting - Survey methods: - consumer survey and opinion poll - Statistical methods:- trend method, barometric projection and econometric method *Different subcategories under these methods *How to conduct ‘market studies and experiment’ (opinion poll method)? Conclusion 00:23:18- 00:23:27 Video by Edupedia World(www.edupediaworld.com), Free Online Education; Click here https://www.youtube.com/playlist?list=PLJumA3phskPFwp2XXInxCWpv28nPMimDU for m...
Video tutorial of forecasting using linear trend line projection
The forecast function in MS Excel can be used to forecast sales, consumer trends and even weight loss! For more details: http://www.familycomputerclub.com/excel/forecast-function-in-excel.html Get the book Excel 2016 Power Programming with VBA: http://amzn.to/2kDP35V If you are from India you can get this book here: http://amzn.to/2jzJGqU
In this video, you will learn how to find out the 3 month and 4 monthly moving average for demand forecasting.
Part 2: http://www.youtube.com/watch?v=5C012eMSeIU&feature=youtu.be Part 3: http://www.youtube.com/watch?v=kcfiu-f88JQ&feature=youtu.be This is Part 1 of a 3 part "Time Series Forecasting in Excel" video lecture. Be sure to watch Parts 2 and 3 upon completing Part 1. The links for 2 and 3 are in the video as well as above.
In this video, you will learn how to find the demand forecast using linear regression.
My 2016 version of my Haunted Garage. I used atmos fx for most of my scary scenes. It came out perfect ! what I used: * 9 foot wide frosted shower curtain purchased at amazon * Mitzubishi XD500U 2200 lumen rear DLP projector. (ebay) * my computer * external computer speakers for sound * VLC media player software used to randomly play effects message me with any questions! This is a very fun project and the kids/adults love it. It's a head turner for sure and it can be done for relatively low money. In the near future i'll be creating a Facebook group page dedicated for this type of display ! There is a growing demand for projection displays and how to videos which I can post.
This is an overview of some basic forecasting methods. These basic forecasting methods are broken into two categories of approaches: quantitative and Qualitative. Quantitative forecasting approaches use historical data and correlative association to make forecasts. Qualitative forecasting approaches look at the opinions of experts, consumers, decision makers and other stakeholders. This video is about basic forecasting methods and covers 9 of the most common approaches. Avercast forecasting software makes good use of these approaches, and is powered by over 200 algorithms. Visit http://www.avercast.com/ for more information on our leading forecasting software.
What is PROJECTION PURSUIT? What does PROJECTION PURSUIT mean? PROJECTION PURSUIT meaning - PROJECTION PURSUIT definition - PROJECTION PURSUIT explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. SUBSCRIBE to our Google Earth flights channel - https://www.youtube.com/channel/UC6UuCPh7GrXznZi0Hz2YQnQ Projection pursuit (PP) is a type of statistical technique which involves finding the most "interesting" possible projections in multidimensional data. Often, projections which deviate more from a normal distribution are considered to be more interesting. As each projection is found, the data are reduced by removing the component along that projection, and the process is repeated to find new projections; this is the "pursuit" aspe...
By popular demand, here is the animation for the "The fatalist", used as a video backdrop on Dark tranquillity's 2010 shows. Painted by Niklas Sundin using Alchemy 0.0.8, screen grabbed and then time stretched to 10-20 times the original painting speed. To see the projection in live action, look to the right.
The video describes using MS Excel to calculate seasonal indices for a very simple set of data that has seasonal fluctuations.
Mulitiplicative seasonally adjusted time series trend forecast
Download file from “Highline BI 348 Class” section: https://people.highline.edu/mgirvin/excelisfun.htm Learn: 1) (00:11) Forecasting using Regression when we see a trend and belief the trend will extend into the future. Will will predict outside the Experimental Region with the Assumption is that trend continues into future. 2) (00:53) Forecast a Trend using Simple Liner Regression. We use the Data Analysis Regression Feature. 3) (03:22) Learn how to use FORECAST function. 4) (08:57) Forecast a Seasonal Pattern using Multiple Regression and three Categorical Variables for quarter using Multiple Linear Regression. We use the Data Analysis Regression Feature. 5) (12:12) VLOOKUP & MATCH functions with Mixed Cell References to populate new categorical variable columns with the Boolean ones and...
Using dummy variables and multiple linear regression to forecast trend and seasonality
Video tutorial of forecasting using linear trend line projection
Population projection, in the field of demography, is an estimate of a future population. In contrast with intercensal estimates and censuses, which usually involve some sort of field data gathering, projections usually involve mathematical models based only on pre-existing data may be made by a governmental organization, or by those unaffiliated with a government
Advertising has never been so polite. LCG allows glass to switch from opaque for privacy and projection to transparent on demand. With switchable glass, you gain 100% utilization of store fronts in retail, bars, restaurants, and other lifestyle establishments. Vizio Projection film allows 180 degree viewing, and produces HD videos and images due to unique LC morphology. Strategic time and location based ads can be programmed in advance to appear and disappear sporadically.
This lesson introduces time series data. We then cover several quantitative time series forecasting methods presenting moving average (MA), weighted moving average (WMA) and exponential models. As we present each type of model we show how to develop the model in Excel (Google Forms). https://ericjjesse.wordpress.com/course-introduction/forecasting-and-regression/
Gauzy LCG ("smart glass") switches from opaque to transparent on demand. When opaque, our product acts as an HD projection surface, which can immediately switch to transparent, allowing full utilization of store front windows. Cohesive branding for worldwide brands with unified messaging, or simple advertisements for SM business. Check out http://gauzy.com/pdlc.html to learn more about the VIZIO Product Line.
Prepared for 7701AFE Economics at the Griffith Business School
Get you Master of Science in Supply Chain Management online in as little as one year. Please visit: business.rutgers.edu/scmonline.
Management Energy Final Presentation Projection of electrical energy Demand and Supply in banten province By Rianti, ridho, Dimas I for Management Energy Class. Engineering Physics UGM 2016- Beta version
Managerial Economics; Management; Demand Forecasting | Techniques of Demand Forecasting; Introduction 00:00:00- 00:00:40 Demand Forecast 00:00:41- 00:02:15 *What is meant by demand forecasting? *The importance of demand forecast How to Forecast Demand? 00:02:16- 00:23:16 *Various steps for demand forecasting *Techniques of demand forecasting - Survey methods: - consumer survey and opinion poll - Statistical methods:- trend method, barometric projection and econometric method *Different subcategories under these methods *How to conduct ‘market studies and experiment’ (opinion poll method)? Conclusion 00:23:18- 00:23:27 Video by Edupedia World(www.edupediaworld.com), Free Online Education; Click here https://www.youtube.com/playlist?list=PLJumA3phskPFwp2XXInxCWpv28nPMimDU for m...
In this video, you will learn how to find the demand forecast using linear regression.
Download file from “Highline BI 348 Class” section: https://people.highline.edu/mgirvin/excelisfun.htm Learn: 1) (00:11) Forecasting using Regression when we see a trend and belief the trend will extend into the future. Will will predict outside the Experimental Region with the Assumption is that trend continues into future. 2) (00:53) Forecast a Trend using Simple Liner Regression. We use the Data Analysis Regression Feature. 3) (03:22) Learn how to use FORECAST function. 4) (08:57) Forecast a Seasonal Pattern using Multiple Regression and three Categorical Variables for quarter using Multiple Linear Regression. We use the Data Analysis Regression Feature. 5) (12:12) VLOOKUP & MATCH functions with Mixed Cell References to populate new categorical variable columns with the Boolean ones and...
Matthew Shum of Cal Tech discusses the use of machine learning ideas in the estimation of discrete choice models, the workhorse model of demand in economics and marketing. He demonstrated the use with large, high-dimensional data sets now available from online markets and large retailers.
If you have questions or comments on the content of this video, please email us at marketing@lpa.com Do you need daily numbers for each property to improve tracking and planning? Are your spreadsheet processes cumbersome and out-of-date? See what the best-of-breed hospitality & hotel property management companies are doing. Here at LPA, we recognize that hospitality property management has its own set of unique necessities and have developed solutions to address the following: * Obtaining and organizing data to generate daily forecasts, * Gaining insight into competitor and market trends integrating sources such as STR data, * Obtaining real-time rollup and consolidation of actuals and forecasts, * Using Cognos Workspace Advanced to do ad-hoc reporting, * Expense allocation at ...
Here's a crash course on how to make your own DFS NBA Projections. The areas emphasis on these projections include projected minutes, points allowed by position and Vegas lines. Check out DFSonDemand.com for more great videos and strategy. My Twitter: https://twitter.com/DFSonDemand To purchase a finished version of my NBA Projections Spreadsheet, visit: http://www.dfsondemand.com/nba-projection-spreadsheets/
Lecture series on Project and Production Management by Prof. Arun kanda, Department of Mechanical Engineering, IIT Delhi. For more details on NPTEL visit http://nptel.iitm.ac.in
More WAV: http://www.wav.media More KORA: https://www.facebook.com/koramusique More Mixmag: http://mixmag.net The Lab NY is Mixmag & WAV's weekly live stream and post-work unwind, powered by Void Acoustics, where we showcase the finest DJs direct from our Bushwick, Brooklyn office. Montreal-based DJ and producer Kora is quickly gaining momentum in the global dance music industry by showcasing a stripped-back and emotive sound profile that works magic on the dancefloor. This lush motif has caught the attention of a collection of respected tastemakers, landing releases on Berlin’s Kindisch imprint, Los Angeles label Sol Selectas and New York’s Earthly Delights. Plus, with his upcoming 'Nous' EP set for release on Anjunadeep later this year, Kora’s undoubtedly an artist to keep an eye on ...
Between driverless cars and AI and gene modification technology, we're about to see a lot of very big changes in a short amount of time. But there's a danger of people rebelling because things moved too fast. Imagine an angry, jobless populace once driverless cars take away the transportation industry and electric cars take away the gas industry. Will politicians have to enact universal basic income? It's a sobering reminder that we are—as a country and as a species—still adapting to an every changing world. Even if it's a world that we designed. Vivek tackles this and a host of other issues (as well as some great things to look forward to) in our first long-form video. Vivek is the author of The Driver in the Driverless Car: How Our Technology Choices Will Create the Future. Intro / Th...
***** Coin Bloq is NOT Paid or Sponsored to Make these Videos ***** ⚡ No donations accepted! But if you would like to support me, please subscribe and consider sharing this vid. Thank you! :) INS EcoSystem, Dec 4, Naga ICO, Ongoing, Envion ICO, Dec 15, QLink, Presale ongoing ($100k?) Bloom Ongoing McAfee Coin N/A ***Please Read the White Papers Before Investing*** ***If You Lose All Your Money We Are Not Liable*** DISCLAIMER: This is not financial advice. We are not Financial advisors. The cryptocurrency space is littered with new and exotic sounding terms - tokenize this, blockchain that, etc. No wonder new entrants to the market gasp in desperatio...
"Long Term Projection of Electricity Generation Sector in East Kalimantan Province" by M. Rizki Kresnawan & Agung Prayogo (MeTSi FT UGM)
Presenter: Prof Rob J Hyndman Slides available: http://robjhyndman.com/talks/melbournerug/ Melbourne R Users: http://www.meetup.com/MelbURN-Melbourne-Users-of-R-Network/ Other R User Group Videos: http://www.vcasmo.com/user/drewconway Info on upcoming book: http://robjhyndman.com/researchtips/fpp/ I will look at the various facilities for time series forecasting available in R, concentrating on the forecast package. This package implements several automatic methods for forecasting time series including foreasts from ARIMA models, ARFIMA models and exponential smoothing models. I will also look more generally at how to go about forecasting non-seasonal data, seasonal data, seasonal data with high frequency, and seasonal data with multiple frequencies. Examples will be taken from my own con...
In this video viewers will learn how to create Work, Cost and Material resources within Microsoft Project. They will learn various methods of assigning resources, the 'Assignment Planning Variables', what 'Effort driven' is, and how to make detailed assignments.
Michele Middlemore, Senior Vice President, MNP LLP, shows you how to build a bottom-up financial model. This pre-revenue model will help you calculate the potential revenue for your company by multiplying the number of likely sales for your product and is the preferred model for angel and VC investors. | Part 1 of 3
Please consider supporting PC Perspective and technical content through our Patreon: http://patreon.com/pcper Subscribe for more hardware videos! http://www.youtube.com/subscription_center?add_user=pcper Full story link: http://www.pcper.com/reviews/Graphics-Cards/GeForce-GTX-1080-8GB-Founders-Edition-Review-GP104-Brings-Pascal-Gamers This is a segment from our GTX 1080 launch day interview with NVIDIA's Tom Petersen.
Oded Schwartz Technical University Berlin January 25, 2010 Algorithms spend time on performing arithmetic computations, but often more on moving data, between the levels of a memory hierarchy and between parallel computing entities. Judging by the hardware evolution of the last few decades, the fraction of running time spent on communication is expected to increase, and with it - the demand for communication-avoiding algorithms. We use geometric, combinatorial, and algebraic ideas and techniques, some of which are known in the context of expander graphs, to construct provably communication-optimal algorithms. For more videos, visit http://video.ias.edu
*Source file included in the description. This video shows you how to create a simple feasibility study. It is based on a 5-years forecast for an IT company that sells two products. The initial assumptions are given. We complete all the required and possible calculations as a first step, set up the financial statements side-by-side, construct investment cashflow statement, and compute the NPV and IRR to lookup the feasibility of the project. The study follows a dynamic approach where the user only needs to change the assumptions later, and it will be reflected on the whole study. Minimal knowledge of MS Excel is sufficient to understand the tutorial. You can find materials related to this video following the links below: *Extension: we add a loan to the study. This affects the forecast...