Questions Answers of analytical chemistry

1. Analytical Chemistry

2. Open Book Mid Term Exam
Question No:1 You have observed 6.18, 4.85, 6.28, 6.49, 6.69 ppm Alkalinity value of
same drinking water sample, now check data for an outlier and calculate mean at
different confidence levels and interpret data?
(a) Find Outlier from the alkalinity of drinking water
(b) Calculate mean at different confidence levels
(c) Interpretation of data
Question No:2 Design and Sketch Randomized sampling and analysis approach for the
estimation of Trehalos in Mango fruit?
(a) Important terms and sampling introduction
(b) Categories of sampling
(c) Randomized Sampling of mango
(d) Random sampling road map/design/sketch of Mango fruit sampling
(e) Analytical approach for estimation of Trehalos in Mango

3. Question No:1 You have observed 6.18, 4.85, 6.28, 6.49, 6.69 ppm
Alkalinity value of same drinking water sample, now check data for an
outlier and calculate mean at different confidence levels and interpret
data?
(a) Find Outlier from the alkalinity of drinking water
(b) Calculate mean at different confidence levels
(c) Interpretation of data
Given Data set: 4.85, 6.18, 6.28, 6.49, 6.69
(a)Find Outlier from the alkalinity of drinking water
Outlier: A data set a appeared to be skewed by the presence of one or more data points
that are not consistent with the remaining data points is called an outlier.
Dixon’s Test: statistical test for deciding if an outlier can be removed from a set of
data.it is used when ‘n’ value is 3 to 7. for greater ‘n’ value Grubb test is used.
General Formula for Q-Test:

4. Solution: In given Data set we use Case-1 of Dixon’s Test because suspected value is smallest in data
set.
Arrange given data from Smallest to largest value
4.85, 6.18, 6.28, 6.49, 6.69
Putting values in Case-1: Suspected value is 4.85

5. (b)Calculate mean at different confidence levels
Confidence Level:
 In statistics confidence limit indicates the probability, with which the estimation of
the location of a statistical parameter for example mean in a sample survey is also
true for the population.
 Confidence levels of 90,95, and 99% are frequently used.
Null Hypothesis: When there is no significant difference between two characteristics of
a population or data generation process. For example when there is no significant
difference between two means/estimates than null hypothesis is accepted.
𝜇1 ≅ 𝜇2
Alternative Hypothesis: When there is significant difference between two characteristics
of a population. For example
𝜇1 ≠ 𝜇2
Null hypothesis is rejected and Alternative hypothesis is retained.

6. At Different Confidence Levels:
At 90% confidence Level:
For N=5 ,
Q calculated is (0.722) which is greater than Q
critical value (0.642) so,
𝑄 𝑐𝑎𝑙 > 𝑄 𝑐𝑟𝑖𝑡
Null hypothesis is rejected and Alternative
hypothesis is accepted
At 95% confidence Level:
For N=5,
Q calculated is (0.722) which is greater than Q
critical value (0.710) So,
𝑄 𝑐𝑎𝑙 > 𝑄 𝑐𝑟𝑖𝑡
Null hypothesis is rejected and Alternative
Hypothesis is accepted
At 99% confidence Level:
For N=5,
Q calculated is (0.722) which is less than Q
critical value (0.821)
𝑄 𝑐𝑎𝑙 < 𝑄 𝑐𝑟𝑖𝑡
Null Hypothesis is accepted and Alternative
hypothesis is rejected

7. (c)Interpretation of Data:
At 90% an 95% confidence level Null hypothesis is rejected and
Suspected value is an outlier. Data point 4.85 is an outlier and
should be discarded.
But at 99% confidence level Null Hypothesis is accepted and
Suspected value is not an outlier. Data point 4.85 is not an
outlier and should be retained.
Outliers are due to Gross errors (that caused by carelessness or
failure of equipment) and we may call them Blunders.

8. Question No:2 Design and Sketch Randomized sampling and analysis approach
for the estimation of Trehalos in Mango fruit?
(a) Important terms and sampling introduction
(b) Categories of sampling
(c) Randomized Sampling of mango
(d) Random sampling road map/design/sketch of Mango fruit sampling
(e) Analytical approach for estimation of Trehalos in Mango
(a) Important terms and sampling introduction
(b) Categories of sampling
Before describing sampling procedure we need to define few key terms
Population: It includes all the members that meet a set of specifications.
Element: A single member of any given population is an element.
Sample: When only some elements are selected from a given larger population we refer it
as sample. It represents the whole population. Its purpose to draw inference.
Census: When all members of the population are selected we call it census.
Sampling: Collections of a group of objects/items from a larger population for
measurement is called sampling. Sampling is process of selecting observations (a sample) to
provide adequate inference about population.
Sampling Frame: Listing of population from which a sample is chosen.

9. Types of Sampling
Probability
sampling/Random
Probability of selection of each
element in population has an
equal and independent chance of
being chosen.
Results obtained are unbiased
Basis of Selection is random
Non-probability sampling/Non-
Random
Nonprobability sampling is a method
of sampling wherein, it is not known that
which individual from the population will be
selected as a sample.
Results obtained are biased
Basis of selection is arbitrarily
• Simple Random sampling
• Stratified sampling
• Systematic sampling
• Cluster random sampling
• Multistage random sampling
• Quota sampling
• Convenience sampling
• Judgmental/purposive sampling

10. (c) Randomized sampling of Mango fruit
 Mango is the second largest crop in Pakistan after citrus, with a
cultivated area of 167.5 hectares of area and production is 1,732
thousand tons. It is grown is 100 countries with 25 millions tones
production.
 Pakistan produces 8.5% world’s mangoes. Sindh and Punjab are major
mango-producing provinces.
 In Punjab, leading districts in mango production are Muzzaffargarh,
Multan, Bahawlpur, and Rahim Yar Khan, which grow major varieties,
such as Langra, Zafran, Sindhri, Dusehri, Desi, Kala, and Sufaid-
Chaunsa.
 According to the Food and Agriculture Organization, the top mango-
producing countries are China, India, Thailand, Indonesia, and the
United States, with Pakistan being ranked number six globally (Food
and Agriculture Organization Report, 2013).
 National fruit of Philippines is carabao mango.
DOI: 10.4238/gmr16029560

11. Sketch of Randomized mango Sampling
if you have a population of 1000 Mangoes, every mango would have odds of 1 in 1000 for getting
selected. Probability sampling gives you the best chance to create a sample that is truly
representative of the population. Population is studied on the basis of mango taste.
Province: Punjab
Cities: Bhakkar
Population of 1000 Mangoes
Determination of sampling Frame
To frame a list include all the members of
population in this list or give them random numbers
 Chaunsa
 Sindhri
 Langra
 Anwar ratool
 Dusehri
 Alphanso
Determine a sampling Procedure(Technique) is
Probability/Random sampling
 Simple Random sampling
 Stratified Sampling
 Cluster Sampling
 Systematic sampling
 Multistage sampling
Population density
Density = (Total number of
individuals of the species in all the
sampling unit (S)/(Total number of
sampling units studied (Q)

12. Five possible ways to collect samples Randomly
Simple Random sampling
 All mangoes from frame can have equal chance of selection/select randomly.
 By simple random sampling we easily analyze the data.
 At each selection, remaining mangoes have equal chance of selection.
 No personal biasness
Methods of Simple random sampling
Lottery Method
The lottery method of creating a
simple random sample is exactly
what it sounds like. A researcher
randomly picks numbers, with each
number corresponding to a subject
or item(mango), in order to create
the sample.
Random number table method
Random number tables have been used in
statistics for tasks such as selected random
samples. This was much more effective than
manually selecting the random samples.
Nowadays, tables of random numbers have
been replaced by computational random
number generators.

13. Stratified Random sampling
 Stratified random sampling is a method of sampling that involves the division of
a population into smaller sub-groups known as strata.
 In stratified random sampling, or stratification, the strata are formed based on
items Or objects (mangoes)attributes or characteristics of population.
 Population divided into homogenous groups.
 Now simple Random sample of mangoes is drawn from each group.
 Stratified sampling highlights the differences between groups which indicates
key characteristics of Mangoes.
 Now sample is randomly drawn from each stratum of mango population.
 Stratified sampling may be proportionate or disproportionate.
Stratum-1
Fully yellow ripened Mangoes
700 mangoes
Stratum-2
100 mangoes with green
patches
Stratum-3
Fully ripened with red patches
150
Stratum-4
50 mangoes are unripen
Stratified Sampling of 1000
mango Population

14. Systematic Random Samplin
 Systematic sampling is a type of
probability sampling method in which
sample members (Mangoes) from a larger
population are selected according to a
random starting point but with a fixed,
periodic interval.
 Most of the time researchers used it
because of it simplicity.
 Mango population contain 1000 mangoes.
When we selected a sample through
systematic way we random select a
mango at starting point but after that
select every mango at regular fixed
interval.
 For example: formula for finding fixed
interval to select the sample
Interval = size of population
 Simple And Convenient
of sampling.
𝒌 =
𝑵
Desired Sample size

15. Cluster Random Sampling
 In this the members of the population are selected randomly, from naturally
occurring groups is called cluster sampling.
 Bifurcation due to naturally occurring groups.
 Selected Cluster treated as sampling unit.
 While in stratified sampling the sampling unit selected randomly from all strata.
 More error chances can be possible.
Consider these are mangoes and
selecting randomly the sample from
all strata.
Consider if these are mango population,
then sampling unit is obtained only from
the two selected clusters/trees.

16. Multistage random sampling
 Sampling scheme that combine several methods together.
 Carried out at various stages.
 It is complex form of cluster sampling.
 It is useful while collecting primary data of mango population from a
geographically dispersed population.
 Population is regarded as made of a number of primary units each of which is
composed of secondary units.
 First stage sampling is done by some suitable method.
 From this first stage , a sub sample is selected from secondary stage units by
same or different methods.

17. Sample in laboratory
Take a sample from all the groups of mangoes like partially ripened, unripen, and
completely ripened fruits.
Determine the sample size in laboratory by statistical methods. Where Mixture of
samples are use for such binary population Bernoulli equation is used to calculate
standard deviation of particle first jar of mangoes labelled as ‘A’. That will be σ𝐴 then
randomly drawn A is determine by Ν =
1−𝑝
𝑝𝜎 𝑟
2
According to Ingamells sampling constant: mass of sample is proportional to number of
particles.
𝐾𝑠 = 𝑚𝑥(𝜎𝑟 𝑥 100)2
After that in laboratory when we determine the standard deviation , then we can use z
values from table and we get: 𝜇 = 𝑥 ± 𝑧𝜎 ÷ 𝑁
Relative uncertainty by 𝜎𝑟 =
𝑡𝑠
𝑥 𝑁
it is tolerable
)100(
ValueCalculated
yUncertaintAbsolute
y(%)UncertaintRelative 

18. (d)Random sampling road map/design/sketch of Mango fruit sampling
Randomized
sampling of
mango fruit
Probability
sampling
Determination
of population
Develop
frame
sample
Choose a
sampling
procedure
• Simple Random sampling
• Stratified sampling
• Systematic sampling
• Cluster random sampling
• Multistage random sampling
Sampling Size
Laboratory
sample
Analytical
approach for
Trehalose
quantification
HPLCGC-MS
Enzymatic method

19. Number of N samples obtained 𝑁 =
𝑡2 𝑠2
𝜎 𝑟
2 𝑥2
The number (N) of observations taken from a population through
which statistical inferences for the whole population are made.
(e)Analytical approach for estimation of Trehalos in Mango
After completing the sampling process Use an appropriate Analytical technique in
Laboratory to quantify Trehalose in Mango fruit
Trehalose sugar
Trehalose (α-d-glucopyranosyl α-d-glucopyranoside) is a non-reducing disaccharide
in which the two d-glucose residues are linked through the anomeric positions to one
another.
 Analytical techniques to quantify Trehalose
 High performance liquid chromatography technique
 Gas-chromatography mass spectrometry
 Enzymatic method (standard enzymatic assay and measuring the change in pH)

20. HPLC:
 High Performance Liquid Chromatography (HPLC) is a form of
column chromatography that pumps a sample mixture or analyte
in a solvent (known as the mobile phase) at high pressure through
a column with chromatographic packing material (stationary
phase).
 HPLC has the ability to separate, find concentration and identify
compounds that are present in any sample that can be dissolved
in a liquid in trace concentrations as low as parts per trillion.
 Because of this versatility, HPLC is used in a variety of industrial
and scientific applications, such as pharmaceutical,
environmental, forensics, and chemicals.GC-MS
 Principle of gas chromatography: The sample solution injected into the
instrument enters a gas stream which transports the sample into a separation
tube known as the "column." (Helium or nitrogen is used as the so-called
carrier gas.) The various components are separated inside the column. The
detector measures the quantity of the components that exit the column.
 To measure a sample with an unknown concentration, a standard sample with
known concentration is injected into the instrument. The standard sample peak
retention time (appearance time) and area are compared to the test sample to
calculate the concentration.

21.  Trehalose a disaccharide in present in mango fruit which is
quantified by GC-MS

22. Thank you!