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  • Statistics Assignment and Homework Help Service

    Tutorhelpdesk

    David Luke

    Contact Us:

    Phone: (617) 807 0926

    Web: www.tutorhelpdesk.com

    Email: - [email protected]

    Facebook: https://www.facebook.com/Tutorhelpdesk

    Twitter: http://twitter.com/tutorhelpdesk

    Blog: http://tutorhelpdesk.blogspot.com/

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    Copyright 2010-2015 Tutorhelpdesk.com

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    About Statistics: Complexity of statistics subject is well

    known. Statistics involves solving complex problems having

    multi-dimensional data using computational methods.

    Information technology has played a vital role in handling and

    simplifying such complex methods and scenarios but students

    face a lot of difficulties in understanding the right application

    of statistical concepts and implementing them using statistical

    softwares. Our Statistics Assignment and Homework help

    service has been strategized and simplified to help students in

    learning statistics problem solving. We use latest and genuine

    tools & softwares to make statistics easy. We deliver step by step help with statistics

    assignments which is self-explanatory to make students understand the method of solving

    problems without any inconvenience.

    Sample Statistics Assignment and Homework Help Service Questions:

    Depreciation Sample Questions

    Question-1: Find the trend line equation and obtain the trend values for the following data

    using the method of the least square. Also, forecast the earning for 2006.

    Year :

    Earning in 000 $

    1997

    38

    1998

    40

    1999

    65

    2000

    72

    2001

    69

    2002

    60

    2003

    87

    2004

    95

    Solution. Here, the number of items being 8 (i.e. even), the time deviation X will be taken

    as

    to avoide the decimal numbers. Thus, the working will run as under:

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    (a) Determination of the Trend Line Equation and the Trend Values

    Working

    The trend line equation is given by Y = a + bX

    Where, a =

    [ = Na + b , and =0]

    = 526

    8 = 65.75

    And b =

    2 [ = a + b 2, and =0]

    = 616

    168 = 3.67 approx.

    Putting the above values of a and b in the equation we get the required trend line equation

    as Yc = 65.75 + 3.67 X

    Where ,trend origin is 2000.5,

    Y unit = annual earning, and X unit = time deviation

    Putting the respective values of X in the above equation, we get the different trend values

    as under:

    Trend Values

    For 1997 When X = -7, Yc = 65.75 + 3.67 (-7) = 40.06

    Year t

    Earnings Y

    Time dvn. i.e. .

    /

    X

    XY X2 Trend values Yc=65.75 + 3.67X

    1997 1998 1999 2000 2000.5 (mid time)

    38 40 65 72 - 69 60 87 95

    -7 -5 -3 -1 0 1 3 5 7

    -266 -200 -195 -72 0 69

    180 435 665

    49 25 9 1 0 1 9 25 49

    40.06 47.40 54.74 62.08 A = 65.75 69.42 76.76 84.10 91.44

    Total 526 0 616 168 N = 8

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    1998 When X = -5, Yc = 65.75 + 3.67 (-5) = 47.40

    1999 When X =-3, Yc = 65.75 + 3.67 (-3) = 54.74

    2000 When X = -1, Yc = 65.75 + 3.67 (-1) = 62.08

    2001 When X =1, Yc = 65.75 + 3.67 (1) = 69.42

    2002 When X = 3, Yc = 65.75 + 3.67 (3) = 76.76

    2003 When X = 5, Yc = 65.75 + 3.67 (5) = 84.10

    2004 When X = 7, Yc = 65.75 + 3.67 (7) = 91.44

    (b) Forecasting of earnings for 2006

    For 2006, X =

    = 20062000 .5

    1

    21

    = 11

    Thus, Yc = 65.75 + 3.67 (11) = 106.12

    Hence, the earnings for 2005 is expected to be

    = $ 106.12 100 = $ 106120

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    Question-2: Obtain the straight line trend equation for the following data by the method of

    the least square.

    Year : Sales in 000 $

    1995 140

    1997 144

    1998 160

    1999 152

    2000 168

    2001 176

    2004 180

    Also, estimate the sales for 2002

    Solution. (a) Determination of the straight line trend equation by the method of least

    square

    Year t

    Sales Y

    Time dvn. i.e. t-1999 X

    XY 2

    1995 1997 1998 1999 2000 2001

    2004

    140 144 160 152 168 176

    180

    -4 -2 -1 0 1 2

    5

    -560 -288 -1 0 1 2

    5

    -16 4 1 0 1 4

    25

    Total 13994 1120 1 412 51 N = 7

    Note. *In the above case, the average of the time variable is given by =

    =

    13994

    7 =

    1999 approx.

    Hence, 1999 has been taken as the year of origin in the above table.

    Working

    The trend line equation is given by Yc = a + bX

    Here, since 0, the value of the two constants a, and b are to be found out by solving

    simultaneously the following two normal equations:

    = Na + b

    = a + b 2

    Substituting the respective values in the above we get

    1120 = 7a + b

    412 = a + 51b

    Multiplying the eqn (ii) by 7 under the eqn (iii) and getting the same deducted from the

    equation (i) we get

    7a + b =1120

    = 7+357=2884

    356= 1764

    b = 1764

    356 = 4.96

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    Putting the above value of b in the equation (i) we get,

    7a + 4.96 = 1120

    7a = 1120 4.96 = 1115.04

    or a = 1115.04/7 = 159.29

    Putting the above values of a and b in the format of the equation we get the straight line for

    trend as under:

    Yc = 159.29 + 4.96X

    Where, the year of working origin = 1999,

    Y unit = annual sales (in 000 $) and

    X unit = time deviations.

    (b)Estimation of the Sale for 2002

    For 2002, X = 2002 1999 =3

    Thus when, X = 3, Yc = 159.29 + 4.96 (3)= 159.29 + 14.88 = 174.17

    Hence, the sales for 2002 are expected to be 174.17 103 = $ 174170.

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    Question-3: Production figures of a Textile industry are as follows:

    Year Production (in units) :

    1998 12

    1999 10

    2000 14

    2001 11

    2002 13

    2003 15

    2004 16

    For the above data.

    (i) Determine the straight line equation by change of the origin under the least square

    method.

    (ii) Find the trend values, and show the trend line on a graph paper, and

    (iii) Estimate the production for 2005 and 2007.

    Solution (i). Determination of the straight line equation by change of the origin under the

    least square method.

    Year T

    Prodn. Y

    Successive values of

    time variable X

    XY Trend values

    T

    1998 1999 2000 2001 2002

    2003 2004

    12 10 14 11 13

    15 16

    1 2 3 4 5

    6 7

    12 20 42 44 65

    90 112

    1 4 9 16 25

    36 49

    10.745 11.50 12.25 13.00 13.75

    14.50 15.25

    Total = 91 =28 = 385 2 = 140 N = 7

    Note. The successive values of time variable X, have been taken as a matter of change of

    the origin to reduce their magnitude for the sake of convenience in calculations.

    Working

    The straight line equation is given by Yc = a + bX

    Here, since 0, we are to work out the values of the two constants, a and b by

    simultaneous solution of the following two normal equations:

    = Na + b

    = a + b 2

    Substituting the respective values obtained from the above table in the above equation we

    get,

    91 = 7a + 28b

    385 = 28a + 140b

    Multiplying the eqn. (i) by 4 under the equation (iii) and subtracting the same from the eqn.

    (ii) we get,

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    28a + 140b = 385

    = 28+112=364

    28=21

    b = 21

    28 = .75

    Putting the above value of b in the eqn. (i) we get,

    7a + 28 (.75) = 91

    = 7a = 91 21 = 70

    a = 70/7 = 10

    Putting the above values of a and b in the relevant equation we get the straight line

    equation naturalized as under:

    Yc = 10 + 0.75 X

    Where, X, represents successive values of the time variable, Y, the annual production and

    the year of origin is 1997 the previous most year.

    (ii) Calculation of the Trend values & Their Graphic Representation

    1998 When X = 1, Yc = 10 + 0.75 (1) = 10.75

    1999 When X =2, Yc = 10 + 0.75 (2) = 11.50

    2000 When X = 3, Yc = 10 + 0.75 (3) = 12.25

    2001 When X =4, Yc = 10 + 0.75 (4) = 13.00

    2002 When X = 5, Yc = 10 + 0.75 (5) = 13.75

    2003 When X = 6, Yc = 10 + 0.75 (6) = 14.50

    2004 When X = 7, Yc = 10 + 0.75 (7)= 15.25

    Graphic Representation of the Trend Line & the Original Data

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    (i) Estimation the Production Figure for 2004 and 2006.

    Since the last successive value of X for 2004 is 7, the successive values of X for 2005 and

    2007 are 8 and 10 respectively.

    Thus, for 2005, when X = 8, Yc = 10 + 0.75 (8) = 16.00

    And for 2007, when X = 10, Yc = 10 + 0.75 (10) = 17.50

    Hence, the estimate figures of production for 2005 and 2007 are 16000 units and 17500

    units respectively.

    Test of Suitability of Straight line Method

    If the differences between the successive observations of a series are found to be constant,

    or nearly so, the straight line model is considered to be a suitable measure for

    representation of trend components, otherwise not. This fact can be determined by the

    method of First Differences illustrated as under:

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    Question-4. State by using the method of First Differences, if the straight line model is

    suitable for finding the trend values of the following time series:

    Year : Sales :

    1997 30

    1998 50

    1999 72

    2000 90

    2001 107

    2002 129

    2003 147

    2004 170

    Solution. Determination of Suitability of the Straight line model by the method of

    First Differences

    Year T

    Sales Y

    First Differences

    1997 1998 1999 2000 2001 2002 2003 2004

    30 50 72 90 107 129 147 170

    50-30 = 20 72 50 = 22 90 72 = 18 107 90 = 17 129 107 = 22 147 129 = 18 170 147 = 23

    From the above table, it must be seen that the first differences in the successive

    observations are almost constant by 20 or nearly so. Hence, the straight line model is quite

    suitable for representing the trend components of the given series.

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    Vi. Parabolic Method of the least square

    This method of least square is used only when the trend of a series is not linear, but

    curvilinear. Under this method, a curve of parabolic type is fitted to the data to obtain their

    trend values and to obtain such a curve, an equation of power series is determined in the

    following model.

    Yc = a + bX + cX2 + dX3 + .+ mXn

    It may be noted that the above equation can be carried to any power of X according to the

    nature of the series. If the equation is carried only up to the second power of X, (i.e. X2) it

    is called the parabola of second degree, and if it is carried up to the 3rd power of X, (i.e.

    X3) it is called the Parabola of 3rd degree. However, in actual practice the parabolic curve of

    second degree is obtained in most of the cases to study the non-linear of a time series. For

    this, the following equation is used.

    Yc = a + bX +cX2

    Where, Yc represents the computed trend value of the Y variable a the intercept of Y, b

    the slope of the curve at the origin of X and c, the rate of change in the slope.

    In the above equation, a, b, and c are the three constants, the value of which are

    determined by solving simultaneously the following three normal equations:

    = + + 3

    It may be noted here that the first normal equation has been derived by multiplying each

    set of the observed relationship by the respective coefficients of a, and getting them all

    totaled ; the second normal equation has been derived by multiplying each set of the

    observed relationship by the respective coefficients of b, and getting them all totaled ; and

    the third equation has been derived by multiplying each set of the observed relationship by

    the respective coefficients of c and getting them all totaled.

    Further, it may be noted that by taking the time deviations from the midpoint of the time

    variable, if and 3 could be made zero, the above three normal equations can be

    reduced to the simplified forms to find the values of the relevant constants as follow :

    From the above, it must be noticed that the value of b can be directly obtained as b =

    ,

    and the values of the other two constants a and c can be obtained by solving simultaneously

    the rst of the following two normal equations:

    a =

    c =

    Once, the values of the three constants a, b and c are determined in the above manner, the

    trend line equation can be fitted to obtain the trend values of the given time series by

    simply substituting the respective values of X therein.

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