NPTEL conducted a public speaking assignment in Week 12 of 2023.
- Assignment 12 was part of this public speaking course.
- The solution for Assignment 12 was presented in the text.
- The year of the assignment was 2023.
📝 Summary:
In Week 12 of 2023, NPTEL conducted Assignment 12 as part of its public speaking course, and the solution for this assignment is provided in the text.
#NPTEL #PublicSpeaking #Assignment12 #Solution #2023
Certainly! Here are the answers with reasons:
1. The two types of data analysis are:
Answer: a. Qualitative and Quantitative
Reason: Data analysis can be broadly categorized into qualitative (dealing with non-numeric data, like text and images) and quantitative (dealing with numeric data) methods.
2. A principle of Qualitative analysis is:
Answer: d. All of these
Reason: Qualitative analysis involves noticing things, thinking about things, and collecting data. All of these principles are essential in qualitative research to gain insights from non-numeric data.
3. The type of ANOVA denoted by the statements is:
Answer: c. Statements I, II, and III
Reason: ANOVA (Analysis of Variance) can be used for one-way analysis, two-way analysis, and K-way analysis, making all three statements correct.
4. The type of data dispersion includes:
Answer: d. All of these (Range, Average absolute deviation, Variance)
Reason: Data dispersion measures the spread or variability in a dataset. Range, average absolute deviation, and variance are all methods to quantify data dispersion.
5. The process by which numerical data is analyzed is known as:
Answer: b. Quantitative analysis
Reason: Numerical data analysis, involving the manipulation and interpretation of numeric data, is known as quantitative analysis.
6. The mathematical equation that is formulated in the form of relationships between variables is known as:
Answer: d. Statistical model
Reason: A statistical model is a mathematical representation used to describe relationships between variables in a dataset.
7. The two types of statistical models are:
Answer: c. Regression and dispersion
Reason: Statistical models can broadly fall into categories like regression models (predictive modeling) and dispersion models (measuring variability).
8. Contingency table is also known as:
Answer: a. Cross tabulation
Reason: A contingency table is often referred to as cross-tabulation, where data is tabulated to show the relationship between two categorical variables.
9. Advances in sensor and connectivity have disabled preventive care.
Answer: b. False
Reason: Advances in sensors and connectivity have enabled and enhanced preventive care through remote monitoring and early detection.
10. Features of IoT Healthcare include:
Answer: d. All of these (Non-invasive monitoring, Cloud-based analytics, Wireless transmission)
Reason: IoT in healthcare offers non-invasive monitoring of patients, utilizes cloud-based analytics for data processing, and facilitates wireless data transmission for real-time monitoring.
11. Components of IoT include:
Answer: d. All of these (Sensing layer, Aggregated layer, Processing layer)
Reason: IoT systems comprise multiple layers, including the sensing layer (sensors and devices), aggregated layer (data aggregation and communication), and processing layer (data analysis and decision-making).
12. An advantage of activity monitoring is:
Answer: b. Long term monitoring
Reason: Activity monitoring can provide continuous and long-term data, allowing for better insights into trends and patterns in a person's activities and health.
13. Deep learning based data analysis can be performed on videos.
Answer: b. False
Reason: Deep learning can be applied to analyze videos, making this statement false. Deep learning models, such as convolutional neural networks (CNNs), are commonly used for video analysis tasks.
14. In-place activity monitoring data analysis is characterized by:
Answer: a. Low power
Reason: In-place activity monitoring typically involves low-power devices or sensors that can operate for extended periods without frequent battery changes or recharging.
15. Processing the handheld activity device data with artificial intelligence can be used for:
Answer: d. All of these (Fall detection, Heart rate detection, Vehicle detection)
Reason: Handheld activity devices, combined with artificial intelligence, can be used for various applications, including fall detection, heart rate monitoring, and vehicle detection, among others.
