quantitive forecasting techniques

Question 1

what is the high low method

Answer 1

technique used to predict an outcome based on another –> predicting a dependant variable

Question 2

when can we use the HL method to estimate the relationship between two variables

Answer 2

when they are quantifiable

Question 3

what would a result of a HL calculation look like

Answer 3

y = a + bx

y= the value for the dependent variable
x = the value for the independent variable
a = that part of y which does not depend on x
b= how much y changes if x changes

Question 4

two advantages of regression analysis

Answer 4

• It uses all the paired data to arrive at a definitive line of best fit.
• We can test the reliability of the analysis for forecasting by estimating
  the degree of correlation there is between the dependent and independent variables.

Question 5

formulae for regression line of best fit

Answer 5

b = ( n∑𝑥y − ∑𝑥∑y) /n∑𝑥2 – (∑x)2
a = ∑y/𝑛 - 𝑏 (∑x /𝑛)

n = the number of pairs of data

Question 6

what are the limitations of forecasts based on regression

Answer 6

• Not all relationships are linear
• Focus on two variables makes it more likely that relevant factors may
  be ignored
• Care should be taken outside of the relevant range – interpolation is
  usually more reliable than extrapolation
• The line of best fit may not have a high correlation

Question 7

what is extrapolation vs interpolation

Answer 7

interpolation refers to determining something whilst the value is in range whereas extrapolation the value lies outside or range

Question 8

what is correlation

Answer 8

Two variables are said to be correlated if a change in the value of one variable is accompanied by a change in the value of the other.

Question 9

what is the correlation coefficient

Answer 9

• The correlation coefficient (r) measures the extent of the linear correlation between two variables.
• The correlation coefficient value will fall within the range of +1 to -1.

Question 10

what does a correlation coefficient close to +1 represent

Answer 10

strong positive correlation

Question 11

what does a correlation coefficient close to zero represent

Answer 11

whether positive or negative the weaker the correlation.

Question 12

explain cause and effect

Answer 12

Correlation describes how one variable moves alongside another. It does not prove that the move in one variable causes a move in the other.

Question 13

what is rank correlation coefficient

Answer 13

measures the correlation between two sets of ranking

Question 14

when can rank correlation be more useful

Answer 14

when it is important to observe relative values of what is being measured rather than value themselves

Question 15

spearman’s rank correlation coefficient

Answer 15

p = 1 - (6∑𝑑^2)/ (𝑛(𝑛^2 − 1))
d = difference between two ranks for an item
n = number of items ranked

Question 16

explain learning effect theory

Answer 16

workforce gains experience in a task so will come to perform it quicker, labour costs reduced over time - not expected to be indefinite

Question 17

conditions necessary for learning effect

Answer 17

• significant manual element
• repetitive
• early stage of production
• consistency in the workforce
• no extensive breaks in production
• motivation of the workers

Question 18

definition of learning effect

Answer 18

every time the cumulative total output of a product doubles, the cumulative average time taken to make all the units to date fellas to a proportion of what it was beforehand

Question 19

definition of learning rate

Answer 19

the proportion to which the cumulative average time per unit falls

Question 20

learning curve formula

Answer 20

y = ax^b

a - time taken to produce the first unit
x - cumulative number of units
b - the index of learning (logLR/log2)
LR = the learning rate (as a decimal

Question 21

what happens when steady sate is reached for time per unit

Answer 21

the time per unit or labour cost per unit becomes a standard cost that can be used for ongoing budgets

Question 22

when does cessation or learning effect arise

Answer 22

usually when one of the assumptions underpinning the theory is no longer applying

Question 23

what is a time series

Answer 23

a sequence of numbers, values, measurements recorded against a timeline

Question 24

wha is benefit of time series analysis

Answer 24

allows observations to be made and conclusions to be drawn about how a variable behaves over time.

Question 25

what are the types of variations which make values more away from trends

Answer 25

seasonal variations
cyclical variations
random variations

Question 26

what is seasonal variations

Answer 26

short term fluctuations in values due to where we are in the planning cycle

Question 27

what is cyclical variation

Answer 27

recurring patterns over a longer period of time

Question 28

what are random variations

Answer 28

irregular or unpredictable variations

Question 29

time series =

Answer 29

tren (Td) x seasonal variations (SV) x other variations (CV+RV)

Question 30

was to calculate trend

Answer 30

• regression analysis
• moving averages

Question 31

how can you estimate some SVs

Answer 31

have to assume that any difference between time series and trend is seasonal

Question 32

limitations of time series analysis

Answer 32

• not all changes relate to time, seasons and cycles
• further ahead we try to forecast, the less reliable the forecast
• historical patterns cannot always be assumes