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 Great! Here are clear, exam-ready answers in simple PGDE style.

(For Q3 the table had one missing frequency. I assumed 5 for 64–72 to keep the distribution symmetric. I show all steps.)


1) Six roles of statistics in education

  • Planning: guides lesson/exam design using past data.

  • Measurement: helps score, grade, and summarize results.

  • Evaluation: compares teaching methods and curricula.

  • Decision-making: supports school policies with evidence.

  • Research: enables data collection, analysis, and inference.

  • Prediction: forecasts enrolment/performance needs.


2) Measurement scales (with uses)

  • Nominal: names/groups only (no order). Example: gender; school house.

  • Ordinal: ordered ranks (unequal gaps). Example: 1st–2nd–3rd position.

  • Interval: equal gaps, no true zero. Example: Celsius temperature.

  • Ratio: equal gaps, true zero. Example: test scores, height, weight.


3) Grouped distribution & Z/Raw conversions

Assumed frequencies:
10–18:2, 19–27:3, 28–36:5, 37–45:9, 46–54:12, 55–63:9, 64–72:5, 73–81:3, 82–90:2.

  • Midpoints (X): 14, 23, 32, 41, 50, 59, 68, 77, 86

  • Total N=50N=50

  • Xˉ=∑fX∑f=50.0\bar X=\dfrac{\sum fX}{\sum f}=50.0

  • SD=∑fX2∑f−Xˉ2≈16.89SD=\sqrt{\dfrac{\sum fX^2}{\sum f}-\bar X^2}\approx 16.89

(a) Convert raw to Z

Z=X−XˉSDZ=\frac{X-\bar X}{SD}
  • For 70%: Z=70−5016.89≈1.18Z=\frac{70-50}{16.89}\approx \mathbf{1.18}

  • For 35%: Z=35−5016.89≈−0.89Z=\frac{35-50}{16.89}\approx \mathbf{-0.89}

(b) Convert Z to raw

X=Z⋅SD+XˉX=Z\cdot SD+\bar X
  • For Z=2: X=2(16.89)+50≈83.77X=2(16.89)+50\approx \mathbf{83.77}

  • For Z=-1.5: X=−1.5(16.89)+50≈24.67X=-1.5(16.89)+50\approx \mathbf{24.67}

(If your missing frequency is different, recompute mean/SD, then apply the same formulas.)


4) (a) Degree of Freedom (df)

Number of values free to vary after fixing a constraint.
For a sample of size nn with a known mean, df=n−1df=n-1.

(b) Three uses of Standard Deviation

  • Measures how spread out scores are.

  • Compares variability between groups.

  • Used to compute Z-scores and confidence intervals.


5) (a) Mean by coding

Data: 15, 18, 21, 24, 27, 30, 33, 36, 42
Let assumed mean A=27A=27, class width c=3c=3.
Codes u=(X−A)/c=−4,−3,−2,−1,0,1,2,3,5u=(X-A)/c = -4,-3,-2,-1,0,1,2,3,5; ∑u=1\sum u=1, n=9n=9.

Xˉ=A+∑unc=27+19⋅3=27.33\bar X=A+\frac{\sum u}{n}c=27+\frac{1}{9}\cdot 3= \mathbf{27.33}

(b) Quota sampling

A non-probability method: divide population into groups (e.g., sex, class) and select participants until each group’s preset quota is filled.


6) Convert to T-scores (Xˉ=45\bar X=45, SD=12SD=12)

T=50+10(X−XˉSD)T=50+10\left(\frac{X-\bar X}{SD}\right)
  • For 79: Z=79−4512=2.83⇒T=50+10(2.83)≈78.3Z=\frac{79-45}{12}=2.83 \Rightarrow T=50+10(2.83)\approx \mathbf{78.3}

  • For 15: Z=15−4512=−2.5⇒T=50+10(−2.5)=25Z=\frac{15-45}{12}=-2.5 \Rightarrow T=50+10(-2.5)=\mathbf{25}



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