FBISE REDUCED ONLINE SYLLABUS
STATISTICS-XI
1. Introduction to Statistics: Collection (1/8) and
Presentation of Data
Content Scope
Nature and Importance of the Science of
Statistics, Statistical Data, Population and
sample. Brief revision of classification,
tabulation and frequency distributions and their
graphic representation
Define Statistics, give importance of
measurements and different fields of science
where measurements are useful. Explain
different types of raw data in the fields of
Science and Humanities, mainly in Medicine,
in Agriculture, in Chemistry and Psychology.
Explain the difference between a population
and a sample, use sketches for showing
population. Explain the importance of the
sample. Demonstrate types of frequency
distributions like symmetrical and nonsymmetrical
Cumulative and relative frequency
distributions be explained by the use of
sketches, Explain bar charts in different forms
namely; divided bar charts, compound bar
charts. Give an explanation for expressing data
in rectangles an pie chart.
2. Measure of Location and Dispersion. (2/8)
Contents Scope
Arithmetic mean, Geometric mean. Median,
Mode, Range, Mean Deviation, Variance,
Standard deviation, Difference between
Absolute and Relative Measures of Dispersion.
Skewness.
Explain arithmetic mean and variance of raw
data from a frequency table, using mid points
and also by change of origin and scale and
their properties. To explain geometric mean,
use ungrouped data as well as grouped data.
Explain the method of direct calculation using
root and also by using logarithms. To explain
median and quantiles graphical method be
explained as well. Mathematical proofs are not
required.
3. Index Number (1/8)
Content Scope
Introduction to Index numbers concept of price
index numbers steps involved in the
construction of price index numbers
“Unweighted price index numbers (fixed based
and chain based method)” weighted price index
Explain the index numbers as a useful
statistical technique to assess the growth or fall
of a certain item or economic series with
respect to time or any other unit. Price index
numbers by simple relative and link relative numbers
(Laspeyer’spaasche’s and fisher’s)
consumer price index number.
methods be explained. Price index and its
constructions must be given as examples.
Fixed base and chain base methods for price
indices be explained. The concept of weights
be explained with reference to the arithmetic
means in grouped data. Laspeyr’s and Fisher’s
indices be explained by applying the standard
results on a number of exercises. Consumer
price index number be explained in general and
with reference to Pakistan. Similarly wholesale price
index numbers to be also explained
in a similar way.
4. Simple Linear Regression and Correlation (1/8)
Contents Scope
Bivariable data (non-random versus random
variable) scatter diagram; estimation of
regression parameters by least squares method,
properties of the regression line; interpretation
and applications of the regression line.
Bivariate data, (random versus random
variable) scatter diagram; point estimation of
population correlation co-efficient; properties
of the sample correlation co-efficient;
interpretation and application.
Explain “Bivariate data”, by giving sketches of
scatter diagrams when one variable is specified
and several values of response variable are
assumed given at each non random variable
similarly the sketches when both variable are
random be also drawn and explained. Least
square method be explained, normal equation
be formed and estimation of regression
parameters be given in terms of X, Y,
XY, Y
2
, and X
2
. Both the regression lines
be explained by considering an example in
which few values of the two variables are
given the properties to be included are :
i. Sum up squares of deviation from
regression line is minimum.
ii. The point of intersection of
regression lines at (X, Y).
Interpret by explaining the use of line of
regression for forecasting and for
estimating at “n” unknown values of
independent variable.
Explain the correlation co-efficient by
explaining bivariate data in which both
variables are random, the calculation of
correlation co-efficient be explained by
considering examples. The properties of
correlations co-efficient be explained by
considering:
i. rxy= ryx
ii. r lying between – 1 and +1.
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iii. the value of correlation co-efficient
does not change by the change of origin
and scale and correlation can be obtained
by geometric mean of the regression coefficient.
5. Analysis of time series (1/8)
Contents Scope
Introduction to the concept of time series;
nature of fluctuations, signal and noise,
components of a time series, measurement of
secular, semi averages, moving averages and
least squares (linear), advantages and
limitations of these methods.
Explain the time series as a series in which one
variable is time occurring at specified intervals
(non random and the other variable is random).
Examples be given from Economics, Public
Administration, Business administration, Trade
and Commerce. Fluctuation in the time series
be explained in terms of trend which is given
in terms of components of a time series and
random fluctuations as noise. Linear and
quadratic forms of time series s be considered.
The linear and quadratic time series be
compared with trend obtained by free hand,
semi averages and moving averages method.