#### Start Date

8-5-2020 12:00 AM

#### Document Type

Poster Session

#### Department

Physics

#### Advisor

Julie Ziffer, PhD

#### Abstract

Data collected by the Sloan Digital Sky Survey is used by many researchers. The success of research projects is dependent on the accuracy of the data, and the validity of the uncertainty interval associated with each data point. The purpose of this project is to assess the uncertainty of SDSS data. A dataset consisting of the light reflectance of different asteroids, at different wavelengths of light, was chosen for analysis. The ratios of the intensity of the different wavelengths being reflected reveals information about the composition of asteroids. The asteroids appear to have a gaussian distribution of these ratios. It’s not clear how the shape of each gaussian is affected by the uncertainty in the data. To obtain a more accurate representation of this distribution, the dataset was partitioned by the size of the uncertainty in each data point. Histogram plots of partial datasets revealed that data with more uncertainty has a wider distribution. By selecting data with the least uncertainty, a more realistic representation of the data distribution was obtained. The refined datasets also reveal how the asteroids can be categorized into different groups. Two of the wavelength ratios that were studied have data distributions that appear to be wide, misshapen gaussians. As the dataset was refined, the histogram plots showed distributions that are clearly two distinct gaussians. This allowed the data to be modeled as the sum of gaussian curves, and for the mean and standard deviation of each curve to be obtained.

#### Open Access?

1

Analyzing The Uncertainty of Sloan Digital Sky Survey Data

Data collected by the Sloan Digital Sky Survey is used by many researchers. The success of research projects is dependent on the accuracy of the data, and the validity of the uncertainty interval associated with each data point. The purpose of this project is to assess the uncertainty of SDSS data. A dataset consisting of the light reflectance of different asteroids, at different wavelengths of light, was chosen for analysis. The ratios of the intensity of the different wavelengths being reflected reveals information about the composition of asteroids. The asteroids appear to have a gaussian distribution of these ratios. It’s not clear how the shape of each gaussian is affected by the uncertainty in the data. To obtain a more accurate representation of this distribution, the dataset was partitioned by the size of the uncertainty in each data point. Histogram plots of partial datasets revealed that data with more uncertainty has a wider distribution. By selecting data with the least uncertainty, a more realistic representation of the data distribution was obtained. The refined datasets also reveal how the asteroids can be categorized into different groups. Two of the wavelength ratios that were studied have data distributions that appear to be wide, misshapen gaussians. As the dataset was refined, the histogram plots showed distributions that are clearly two distinct gaussians. This allowed the data to be modeled as the sum of gaussian curves, and for the mean and standard deviation of each curve to be obtained.