Bissoy.com
Doctors Medicines MCQs Q&A

When a set of data has suspect outliers, which of the following are preferred measures of central tendency and of variability?

When a set of data has suspect outliers, which of the following are preferred measures of central tendency and of variability? Correct Answer median and interquartile range

(E) The mean, standard deviation, variance, and range are all affected by outliers; the median and interquartile range are not.

Related Questions

In a murder case, police rounded up four suspects and one of those is surely a killer. These four suspects made the following statements: Suspect A said, “I am not the killer”. Suspect B said, “I am the killer”. Suspect C said, “A is the killer”. Suspect D said, “C is lying”. If out of the given four statements, only one statement is correct, then identify who is the real killer?
Graphical statistics, measures of central tendency, and measures of variability, are . . . . . . . .
Principle: A defamatory statement is one which has a tendency to injure the reputation of the person to whom it refers to. Defamation is of two kinds-
(1) Libel, when the defamatory statement is in some permanent and visible form and
(2) Slander, when it is in some trasitefy form, visible or audible. Libel is actionable per se, but slander is actionable only on proof of actual damage.
Factual Situation: A person accused of a crime is arrested by the police. The police give an open statement that the suspect had an extra-marital affair. It is subsequently proved in court that the suspect was innocent of the crime. Will the accused succeed if he files a civil suit for defamation, claiming compensation against the police?
Which of these can be used as the estimate of standard deviation of total variability which is including both product variability, and the gauge variability?
If a distribution of scores includes one or more outliers, which of the following measures of central tendency should be used?
Which of the following statements are true?
Statement I Big data refers to no precise quantity, but generally refers to data in the range of Petabytes and Exabyte, i.e. billions to trillions of records, all from various sources. Big data is generated much faster. than traditional data in much larger quantities.
Statement II Big data interests industries because they are able to learn more patterns and curious variances than smaller data sets, with the capability to provide valuable insights into consumer behaviour, weather systems, financial market activity, or other phenomena.
Statement III Various departments and product lines use various applications within most organisations and store data in separate datasets. These separate databases may contain similar data, but data from one data base to another is not always consistent. This is called data silo.
Which of the following terms means the tendency of a supervisor to rate a subordinate lower than his performance? 1. Horns Effect 2. Halo Effect 3. Central Tendency 4. Pointing Tendency
You use Microsoft Visual Studio 2010 and Microsoft .NET Framework 4 to create anapplication. The application uses the ADO.NET Entity Framework to model entities. Theapplication allows users to make changes to entities while disconnected from the central data store. You need to ensure that when the user connects to the central data store and retrieves new data, the application meets the following requirements:
  • Changes made to the local data store in disconnected mode are preserved.
  • Entities that have already been loaded into the local data store, but have not been modified by the user, are updated with the latest data.
What should you do?
Suppose on performing reduced error pruning, we collapsed a node and observed an improvement in the prediction accuracy on the validation set. Which among the following statements are possible in light of the performance improvement observed? (a) The collapsed node helped overcome the effect of one or more noise affected data points in the training set (b) The validation set had one or more noise affected data points in the region corresponding to the collapsed node (c) The validation set did not have any data points along at least one of the collapsed branches (d) The validation set did have data points adversely affected by the collapsed node
which of the following cases will K-Means clustering give poor results?
1. Data points with outliers
2. Data points with different densities
3. Data points with round shapes
4. Data points with non-convex shapes