Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Microsoft Excel: Regression Analysis01:18

Microsoft Excel: Regression Analysis

Regression analysis in Microsoft Excel is a powerful statistical method for examining the relationship between a dependent variable and one or more independent variables. It's used extensively in fields such as economics, biology, and business to predict outcomes, understand relationships, and make data-driven decisions. The most common type is linear regression, which attempts to fit a straight line through the data points to model the relationship between variables.
To perform regression...
Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
Microsoft Excel: Pearson's Correlation01:18

Microsoft Excel: Pearson's Correlation

Microsoft Excel is a powerful tool for statistical analysis, including calculating Pearson's correlation coefficient, which measures the strength and direction of a linear relationship between two continuous variables. Pearson's correlation coefficient, often denoted as "r," ranges from -1 to 1. A value close to 1 indicates a strong positive correlation, meaning as one variable increases, the other does too. A value close to -1 indicates a strong negative correlation, implying that as one...
Performing a Simple Data Analysis using MS-Excel Function01:17

Performing a Simple Data Analysis using MS-Excel Function

Microsoft Excel offers a suite of functions and tools ideal for statistical analysis, making it accessible to students and researchers. This article outlines fundamental Excel functions pivotal for data analysis.
SUM: This function calculates the total sum of a range of values. It's the foundation for aggregating data, essential for determining overall trends and totals in datasets.
AVERAGE: It computes the mean value of a given set of numbers, providing a quick insight into the central...
Curve Equations01:17

Curve Equations

Curves are essential geometric elements characterized by tangent distance, chord length, middle ordinate, and total arc length. These measurements are crucial in understanding a curve's geometric and spatial properties and are defined by the relationship between its radius and its central angle.The tangent distance (T) refers to the straight-line measurement from the intersection point of two tangents to either the start or end of the curve. This distance is influenced by the curve's radius (R)...
Area Between Curves: Problem Solving01:27

Area Between Curves: Problem Solving

A region can be enclosed by three curves: a square root function, a reflected cube root function, and a linear function. The linear function intersects each of the other two curves, and these intersection points determine where the boundary of the enclosed region changes. Because different curves serve as the upper and lower boundaries in different parts of the graph, the area cannot be found using a single setup over the entire interval.To compute the area, the region is first divided into two...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Partial cranial internal hemipelvectomy in a feline patient with ilial osteosarcoma - a case report.

The Journal of small animal practice·2026
Same author

The rate of non-sentinel lymph node metastases at axillary dissection in patients with a positive sentinel lymph node after neoadjuvant chemotherapy.

Surgical oncology·2026
Same author

Increasing the proportion of grazed grass in the diet in early lactation and its impact on enteric methane emissions and rumen fermentation of pasture-based dairy cows.

Animal : an international journal of animal bioscience·2026
Same author

Perioperative Frailty: The need for a novel and collaborative approach.

Irish medical journal·2025
Same author

Cross-sectional analysis of the associations between age and body weight at first calving and productivity in spring-calving Holstein-Friesian dairy cows.

Animal : an international journal of animal bioscience·2025
Same author

Acute generalized exanthematous pustulosis: European expert consensus for diagnosis and management.

Journal of the European Academy of Dermatology and Venereology : JEADV·2024
Same journal

Tailoring oxygen vacancy of WO<sub>3</sub> nanoparticles for high-performance gas sensing: room-temperature NO<sub>2</sub> and low-temperature triethylamine detection.

Talanta·2026
Same journal

Mixed potential acetone sensor based on LaBaCo<sub>2-x</sub>Fe<sub>x</sub>O<sub>5±δ</sub> (x=0, 0.05 and 0.2) sensing electrode and yttria-stabilized zirconia for non-invasive diagnosis of diabetes.

Talanta·2026
Same journal

A nanowire-based fluorescent sensor for detecting hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>) dyshomeostasis in cell body and synapse of Alzheimer's disease (AD) cell model.

Talanta·2026
Same journal

Ultra-sensitive determination of cyclopiazonic acid in complex food samples via competitive time-resolved luminescence immunoassays coupled to green microextraction.

Talanta·2026
Same journal

Integrated analytical characterization and multiscale modeling of supramolecular interactions in lumefantrine-curcumin coamorphous systems with enhanced biopharmaceutical and anticancer performance.

Talanta·2026
Same journal

Pixel-wise assessment of industrial compost transformation by NIR hyperspectral imaging and chemometrics: an early-warning tool for process monitoring.

Talanta·2026
See all related articles

Related Experiment Video

Updated: Jun 28, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

Non-linear curve fitting using Microsoft Excel solver.

S Walsh1, D Diamond

  • 1School of Chemical Sciences, Dublin City University, Dublin 9, Ireland.

Talanta
|April 1, 1995
PubMed
Summary
This summary is machine-generated.

Microsoft Excel Solver effectively models non-linear equations for analytical data. Its accessible interface and dynamic display make it ideal for teaching iterative curve fitting techniques.

More Related Videos

Visualizing Intracellular SNARE Trafficking by Fluorescence Lifetime Imaging Microscopy
08:55

Visualizing Intracellular SNARE Trafficking by Fluorescence Lifetime Imaging Microscopy

Published on: December 29, 2017

Related Experiment Videos

Last Updated: Jun 28, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

Visualizing Intracellular SNARE Trafficking by Fluorescence Lifetime Imaging Microscopy
08:55

Visualizing Intracellular SNARE Trafficking by Fluorescence Lifetime Imaging Microscopy

Published on: December 29, 2017

Area of Science:

  • Analytical Chemistry
  • Computational Chemistry

Background:

  • Non-linear equations are common in analytical chemistry.
  • Specialized software is often required to solve these equations.
  • Microsoft Excel's Solver tool offers a potential solution.

Purpose of the Study:

  • To evaluate Microsoft Excel's Solver for solving non-linear equations.
  • To assess its suitability for data modeling in analytical chemistry.
  • To determine its potential as a teaching tool for curve fitting.

Main Methods:

  • Testing Solver with various analytical data sets (e.g., chromatography, FIA, fluorescence, ISE).
  • Analyzing the performance and user interface of Solver.
  • Comparing Solver to commercial 'black-box' packages.

Main Results:

  • Solver successfully models data from diverse analytical situations.
  • The user-friendly interface and dynamic display aid in understanding iterative processes.
  • Excel's widespread availability makes Solver an accessible tool.

Conclusions:

  • Solver is a viable and accessible tool for non-linear equation solving and data modeling in analytical chemistry.
  • Its features support the teaching of iterative non-linear curve fitting principles.
  • It offers users greater control over the modeling process compared to some commercial alternatives.