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    Multivariate, Time-Series, and Survival Analysis

    Multivariate statistics is a form of statistics encompassing the simultaneous observation and analysis of more than one outcome variable. The application of multivariate statistics is multivariate analysis. Multivariate statistics is concerned with understanding the different aims and background of each of the different forms of multivariate analysis and how they relate to each other. It is also concerned with multivariate probability distribution in terms of how these can be used to represent the distribution of observed data and how they can be used as part of statistical inference, where several different quantities are of interest to the same analysis.

    A time series is a sequence of data points measured at successive points in time spaced at uniform time intervals.  Time series are used in statistics, signal processing, pattern recognition, econometrics, mathematical finance and many more. Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistic and other characteristics of the data. Time series forecasting is the use of a model to predict future values based on previously observed values.

    Survival analysis a branch of statistics that deals with the analysis of time to events; for example, the death in biological organisms and failure in mechanical systems. This topic is called reliability theory. Survival analysis also attempts to answer the questions of that is the proportion of a population which will survive past a certain time, or can multiple causes of death or failure be taken into account. Survival analysis involves the modeling of time to event data. Reoccurring events or repeated event models relax assumptions that only a single event occurs for each subject. 

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    BrainMass Categories within Multivariate, Time-Series, and Survival Analysis

    Time Series Analysis

    Solutions: 53

    A time series is a sequence of data points measured at successive points in time spaced at uniform time intervals.

    BrainMass Solutions Available for Instant Download

    Linear Trend Forecast Analysis

    For the time series below a) Develop a linear trend forecast b) Add a quadratic component to the model in part (a) and develop a new forecast c) Now assume a seasonal pattern and add the seasonality of the months to the linear trend model in part (a) and develop a new forecast d) Provide t

    Forecasting of a Time Series, using Excel

    For this case study we will consider a company that sells cars (Car Dealer). The goal is to decompose the seasonality of the data represented by car sales. Data were collected quarterly for a period of 3 years. Thus, being quarterly data we will consider a moving average of order 4, and for the centering of the moving average we

    Yearly Forecast Analysis

    Perform an exponential smoothing forecast with α=0.3 with the following data. Use the demand for the month of January for the initial forecast. Month Demand January 21 February 23 March 34 April 32 May 33 June 35 July 30 August 26 September 24 October 25 November 26 Decemb

    Forecasting: Graphing Trends

    1) Plot the following time series to determine which of the trend models appears to fit better. Period 1 2 3 4 5 6 7 8 9 10 Time Series 55 57 53 49 47 39 41 33 28 20 2) The following trend line and seasonal indexes were computed from 4 weeks of daily observations. Forecast the 7 values for next week. y=120 + 2.3t t=1,2..

    Reliability of a Series System Problem

    An engine system consists of three main components in a series, all having the same reliability. Determine the level of reliability required for each of the components if the engine is to have a reliability of 0.998.

    Simple Exponential Smoothing Forecast Method for units

    You are given that the forecast for the current period of 70 turned out to be 6 units less than the actual demand. The forecast for the next period is 75.8. What must alpha equal (rounded to 4 decimals) if a simple exponential smoothing forecast method were being used?

    Exponential Smoothing Forecast

    Given the following data, use exponential smoothing with a=0.2 and a=0.5 to generate forecasts for periods 2 through 6. Use MAD and MSE to decide which of the two models produced a better forecast. Period Actual Forecast 1 15 17 2

    Seasonally Adjusted Forecast

    Small Wonder, an amusement park, experiences seasoned attendance. It has collected two years of quarterly attendance data and made a forecast of annual attendance for the upcoming year. Compute the seasonal indexes for the four quarters and generate quarterly forecasts for the coming year, assuming annual attendance for the comi

    Operations Management: Forecast Trend

    A manufacturer of printed circuit boards uses exponential smoothing with trend to forecast monthly demand of its product. At the end of December, the company wishes to forecast sales for January. The estimate of trend through November has been 200 additional boards sold per month. Average sales have been around 1000 units per mo

    Forecast: Monthly Index

    Each worker's monthly caseload is determined by the number of cases received and the number of workers available during the month. There are two excel spreadsheets attached. One shows the number of cases for each month, number of staff who reported to work, and the caseload per worker for each of the past 48 months. The other

    Forecast Analysis

    The Bayside Fountain Hotel is adjacent to County Coliseum, a 24,000 seat arena that is home to the city's professional basketball and ice hockey team and that host a variety of concerts, trade shows and conventions throughout the year. The hotel has experienced the following occupancy rates for the past 9 years, since the colise

    Exponentially Smoothed Forecast, MAD, MAPD in EXCEL

    The manager fo the Petroco Service Station wants to forecast the demand for unleaded gasoline next month so that the proper number of gallons can be ordered from the distributor. The owner has accumulated the following data on demand for unleaded gasoline from sales during the past ten months: Month Gas

    Development of a Forecasting Chart

    I have tried several times and missing a step somewhere in the process. Rosa's Italian restaurant wants to develop forecasts of daily demand for the next week. The restaurant is closed on Mondays and experiences a seasonal pattern for the other six days of the week. Mario, the manager has collected information on the number o

    Operations Management (Forecasting)

    A manager receives a forecast for next year. Demand is projected to be 600 units for the first half of the year and 900 units for the second half. The monthly holding cost is $2 per unit, and it costs an estimated $55 to process an order. a. Assuming that monthly demand will be level during each of the six-month periods cover

    Holt-Winters method forecasting problem

    3-25. The number of cases of merlot wine sold by a Paso Robles winery in an 8-year period follows: Year Cases of Wine 1991 270 1992 365 1993 389 1994 456 1995 358 1996 500 1997 410 1998 376 Referring to the Table above, the Holt-Winters method for forecasting with smoothing constant of 0.2 for both level and tren

    Upper and Lower control limits

    1. Which of the following situations suggest a process that appears to be operating in a state of statistical control? a. A control chart with a series of consecutive points that are above the center line and a series of consecutive points that are below the center line. b. A control chart in which no points fall outside

    Forecasting Model Approaches

    In selecting an appropriate forecasting model, the following approaches are suggested: a. perform a residual analysis. b. measure the size of the forecasting error. c. use the principle of parsimony. d. all of the above.

    The Omni Hotel: Forecast future occupancy rate

    1. The Omni Hotel in Charleston SC wants to forecast their expected occupancy rate for the next 5 years. Using the past data below, forecast the hotel's future occupancy. Year Occupancy Rate (%) 1 82 2 77 3 76 4 80 5

    Linear Trend Forecasts in Excel

    The Dean of the business college at Strayer University wants to forecast the number of students who will enroll in business courses at the Charleston SC campus. Historically the enrollments have been: Year Students 1 400 2 450 3

    Time-Series line chart

    Use Excel or MegaStat to make an attractive, well-labeled time-series line chart. Adjust the Y-axis scale if necessary to show more detail (since Excel usually starts the scale at zero). If a fitted trend is called for, use Excel's option to display the equation and R2 statistic. Include printed copies of all relevant graphs w

    Average Starting Salaries for Students

    Average starting salaries for students using a placement service at a university have been steadily increasing. A study of three graduating classes indicates the following average starting salaries: Year Actual Forecast 2002 $20,000 $20,000 2003 $22,000 $20,000 2004 $23,000 ? 18. What

    Exponential Smoothing Forecast.

    16. Look at the attached spreadsheet....Use excel or QM to do exponential smoothing to compute miles for weeks 2 through 12, assuming an initial forecast for week 1 of 17,000. Use alpha of 0.2. What is the forecast demand for week 5? A. 15 B. 19 C. 25 D. 30 17. See attached spreadsheet...What is the MAD for this model?

    Model of Interaction

    Use the information given below: Factor A - + Factor B - 3 7 + 8 ? Fill in the blank cell above using the additive model of interaction: Answer is 12. No problem with the additive model. It is the multiplicative mode of interaction answ

    Forecasting Demand Each Season

    1000 tires sold on average each of the past few years. the past 2 years 200 and 250 respectively in the fall season, 300 and 350 in the winter season, 150 and 165 in the spring season, and 300 and 285 in the summer season. Projected sales next year are 1200. What will the demand be each season? I would like this in a

    Calculating forecast based on a given trend equation

    The manager of a company believed that her company's profits were following an exponential trend. She used Microsoft Excel to obtain a prediction equation for the logarithm (base 10) of profits: Log10(Profits) = 2=0.3X The data she used were from 1993 through 1998, coded 0 to 5. The forecast for 1999 profits is ________.

    Calculating forecast based on trend equation

    Excel was used to obtain the following quadratic trend equation: Sales = 100 - 10X + 15X2 The data used was form 1989 through 1998, coded 0 to 9. The forecast for 199 is_________ A. 1,225 B. 980 C. 1,500 D. 1,600

    The following table contains the number of complaints

    The following table contains the number of complaints received in a department store for the first 6 months of last year. Month Complaints January 36 February 45 March 81 April 90 May 108 June 144 Referring to the table above, if this series is smoothed using exponential smoothing with a smoothing constant of 1/3, wh

    Time Series Problem

    (See attached file for full problem description) --- Let {Z(s), s } is a stationary process. Define Suppose (Z(s1),....,Z(sn)) is observed at know locations {s1,....,sn}. Please find an optimal linear prediction of Z(s) based on the observations and function. How would you estimate function from the observations? ---

    the dependent variable sed.

    This generic question is posed: You have timed the rate at which participants can solve puzzles under three conditions of noise: high, medium,low. In addition, the participants are under the influence of either marijuana, caffeine, or alcohol. What kind of design do you have? a. A 2X3 between-subjects factorial design b.