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Description

Topics covered in this session:

1. What is Statistics?

The branch of mathematics that deals with the collection, organization, analysis, and interpretation of numerical data. Statistics is especially useful in drawing general conclusions about a set of data from a sample of the data.

2. Things we do with a data in statistics:
- Data Collection
- Organization
- Analysis
- Interpretation
- Presentation

This particular video deals with all the basic of how to collect the data, what are the ways to organize the data that you have received and how you can present the data.

Well, just organizing the data is not sufficient, we should also know how to analyse the data to interpret the results that you need.

After watching this video, you might also be interested in our other statistics related videos,

2. Mean of Grouped Data

3. Mean of Grouped Data Problem Solving 1 (Direct method)

4. Mean of Grouped Data Problem Solving 2 (Assumed Mean method)

5. Mean of Grouped Data Problem Solving 3 (Step deviation method)

6. Median of Grouped Data - Problem Solving

7. Mode of Grouped Data - Problem Solving

8. Cumulative Frequency - Less than type Ogive

9. Cumulative Frequency - More than type Ogive

We also have a booklet for the same. The booklet again gives a quick glance about everything with a variety of questions to solve and study.

Statistics | Assessments and Worksheets

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Mathematics - Statistics for Beginners - Introduction Algebra

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6th - 10th
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Duration
4:10

Description

Topics covered in this session:

1. What is Statistics?

The branch of mathematics that deals with the collection, organization, analysis, and interpretation of numerical data. Statistics is especially useful in drawing general conclusions about a set of data from a sample of the data.

2. Things we do with a data in statistics:
- Data Collection
- Organization
- Analysis
- Interpretation
- Presentation

This particular video deals with all the basic of how to collect the data, what are the ways to organize the data that you have received and how you can present the data.

Well, just organizing the data is not sufficient, we should also know how to analyse the data to interpret the results that you need.

After watching this video, you might also be interested in our other statistics related videos,

2. Mean of Grouped Data

3. Mean of Grouped Data Problem Solving 1 (Direct method)

4. Mean of Grouped Data Problem Solving 2 (Assumed Mean method)

5. Mean of Grouped Data Problem Solving 3 (Step deviation method)

6. Median of Grouped Data - Problem Solving

7. Mode of Grouped Data - Problem Solving

8. Cumulative Frequency - Less than type Ogive

9. Cumulative Frequency - More than type Ogive

We also have a booklet for the same. The booklet again gives a quick glance about everything with a variety of questions to solve and study.

Statistics | Assessments and Worksheets

Report this resource to TPT
Reported resources will be reviewed by our team. Report this resource to let us know if this resource violates TPT's content guidelines.

Reviews

5.0
Rated 5 out of 5, based on 1 reviews
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rating
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Rated 5 out of 5
June 8, 2019
All I wanted to understand in short was here. Clear n simple. Thanks
Vani R.
1 review

Questions & Answers

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Standards

to see state-specific standards (only available in the US).
Understand that statistics can be used to gain information about a population by examining a sample of the population; generalizations about a population from a sample are valid only if the sample is representative of that population. Understand that random sampling tends to produce representative samples and support valid inferences.
Use data from a random sample to draw inferences about a population with an unknown characteristic of interest. Generate multiple samples (or simulated samples) of the same size to gauge the variation in estimates or predictions. For example, estimate the mean word length in a book by randomly sampling words from the book; predict the winner of a school election based on randomly sampled survey data. Gauge how far off the estimate or prediction might be.
Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the centers by expressing it as a multiple of a measure of variability. For example, the mean height of players on the basketball team is 10 cm greater than the mean height of players on the soccer team, about twice the variability (mean absolute deviation) on either team; on a dot plot, the separation between the two distributions of heights is noticeable.
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