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Related Concept Videos

Confidence Intervals01:21

Confidence Intervals

10.8K
An unbiased point estimate is often insufficient to predict a population estimate, such as population mean or population proportion. In this scenario, a confidence interval is used. A confidence interval is an estimate similar to a  sample proportion. However, unlike the point estimate which is a single value, the confidence interval  contains a range of values. These values have lower and upper limits, known as confidence limits, and can be designated as L1 and L2, respectively.
A...
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Interpretation of Confidence Intervals01:19

Interpretation of Confidence Intervals

10.2K
A confidence interval is a better estimate of the population than a point estimate, as it uses a range of values from a sample instead of a single value.
Confidence intervals have confidence coefficients that are crucial for their interpretation. The most common confidence coefficients are 0.90, 0.95, and 0.99, which can be written as percentages–90%, 95%, and 99%, respectively.
Suppose a person calculates a confidence interval with a confidence coefficient of 0.95. In that case, they can...
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Uncertainty: Confidence Intervals00:54

Uncertainty: Confidence Intervals

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The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
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Confidence Interval for Estimating Population Mean01:25

Confidence Interval for Estimating Population Mean

9.0K
A point estimate of the population mean is obtained from a single sample. Such a point estimate does not represent a population well because it needs to account for variability in the population. Single point estimate can also be biased despite the sample being selected randomly. Thus, a point estimate is often unreliable. A confidence interval is needed to reduce this unreliability.
A confidence interval for the mean is a range of values that provides an estimate of the population mean. As the...
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Standard Error of the Mean01:13

Standard Error of the Mean

12.5K
The sampling variability of a statistic is defined as how much the statistic varies from one sample to another. The sampling variability of a statistic is typically measured by measuring its standard error.
The standard error of the mean is an example of a standard error. It is a unique standard deviation known as the standard deviation of the sampling distribution of the mean. The standard error of the mean is a statistic that calculates how correctly a sample distribution represents a...
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The Scientific Method03:50

The Scientific Method

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Chemistry is an empirical science. Scientists often pose questions to understand the chemistry in everyday life and seek answers to these questions. To achieve this, scientists follow a definitive series of steps that together make up the Scientific Method. This approach involves making observations, asking questions, building a hypothesis, conducting experiments, analyzing results, and forming a conclusion. 
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Related Experiment Video

Updated: Feb 15, 2026

Evaluation of the Productivity of Social Wasp Colonies Vespinae and an Introduction to the Traditional Japanese Vespula Wasp Hunting Technique
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WASP (Write a Scientific Paper) using Excel - 6: Standard error and confidence interval.

Victor Grech1

  • 1Academic Department of Paediatrics, Mater Dei Hospital, Malta.

Early Human Development
|February 6, 2018
PubMed
Summary

Learn to calculate standard error and confidence intervals in Microsoft Excel. This guide simplifies essential inferential statistics for accurate data analysis.

Keywords:
BiostatisticsComputersSoftwareStatistics

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Area of Science:

  • Statistics
  • Data Analysis

Background:

  • Descriptive statistics are fundamental to inferential statistics.
  • Standard error and confidence intervals are key components of data analysis.

Purpose of the Study:

  • To provide guidance on calculating standard error and confidence intervals.
  • To demonstrate these calculations using Microsoft Excel.

Main Methods:

  • Utilizing Microsoft Excel functions for statistical calculations.
  • Step-by-step instructions for implementing formulas.

Main Results:

  • Successful calculation of standard error.
  • Accurate computation of confidence intervals.

Conclusions:

  • Microsoft Excel can be effectively used for statistical analysis.
  • Simplifies complex statistical calculations for researchers.