Using the standard grouped-data interpolation formula with position 3N/4, estimate the third quartile Q₃ of the temperature distribution.Temperature (°C) Number of stations 0–10 1 10–20 2 20–30 3 30–40 4 40–50 5 50–60 4 60–70 3 70–80 2 80–90 1
59.375°C
Here \(N=25,\quad 3N/4=18.75\). The third quartile lies in 50–60°C, whose preceding cumulative frequency is 15, frequency is 4 and width is 10°C. Therefore \(Q_3=50+\frac{18.75-15}{4}\times10=59.375^\circ\mathrm{C}\).
Important Questions from Data Analysis - Teaching
Given below are two statements:
Statement I: In two tail test, 2.5% of the area of the normal curve falls on the right of 1.96 standard deviations above the mean and 2.5% to the left of 1.96 standard deviations below the mean.
Statement II: In one tail test, for testing the difference between large sample means, a z score of 1.64 is taken as Yardstick at the 5% level of significance.
In light of the above statements, choose the most appropriate answer from the options given below:
In a traditional extract–transform–load (ETL) workflow, data scrubbing performed during the transformation stage is:
Temperature (°C) Number of stations 0–10 1 10–20 2 20–30 3 30–40 4 40–50 5 50–60 4 60–70 3 70–80 2 80–90 1 Using class midpoints, what is the estimated arithmetic mean temperature?
Temperature (°C) Number of stations 0–10 1 10–20 2 20–30 3 30–40 4 40–50 5 50–60 4 60–70 3 70–80 2 80–90 1 Using the standard grouped-data interpolation formula, what is the estimated median temperature?
S.No. Temperature/°C Numbers of stations 1 0-10 1 2 10-20 2 3 20-30 3 4 30-40 4 5 40-50 5 6 50-60 4 7 60-70 3 8 70-80 2 9 80-90 1 Answer the following questions on the basis of above table
The number of stations that recorded temperature less than 40°C:
