Fig. 5. Relationship between duration of asbestos exposure and maximum pleural plaque length in occupational and environmental asbestos exposure groups,

Slides:

Advertisements

Similar presentations

Simple linear models Straight line is simplest case, but key is that parameters appear linearly in the model Needs estimates of the model parameters (slope.

Advertisements

1. What is the probability that a randomly selected person is a woman who likes P.E.? 2. Given that you select a man, what is the probability that he likes.

Statistics 350 Lecture 21. Today Last Day: Tests and partial R 2 Today: Multicollinearity.

Figure 1.1 The observer in the truck sees the ball move in a vertical path when thrown upward. (b) The Earth observer views the path of the ball as a parabola.

All about Regression Sections Section 10-4 regression Objectives ◦Compute the equation of the regression line ◦Make a prediction using the.

March 2006TAAPT conference Long Term Analysis of 20 MHz Solar Radio Events P. Mason, M. Villarreal, Dr. C. Higgins MTSU Department of Physics and Astronomy.

Basic Statistics. Basics Of Measurement Sampling Distribution of the Mean: The set of all possible means of samples of a given size taken from a population.

In the above correlation matrix, what is the strongest correlation? What does the sign of the correlation tell us? Does this correlation allow us to say.

Dr. Fowler AFM Unit 8-5 Linear Correlation Be able to construct a scatterplot to show the relationship between two variables. Understand the properties.

Spatial Interpolation of monthly precipitation by Kriging method

Get out your Interpretation WS! You will be able to predict values based on a regression line. You will be able to communicate the risk in extrapolation.

Bivariate data are used to explore the relationship between 2 variables. Bivariate Data involves 2 variables. Scatter plots are used to graph bivariate.

“Numbers are like people… torture them long enough and they’ll tell you anything...” Linear transformation.

Algebra 3 Lesson 1.9 Objective: SSBAT identify positive, negative or no correlation. SSBAT calculate the line of best fit using a graphing calculator.

SWBAT: Calculate and interpret the residual plot for a line of regression Do Now: Do heavier cars really use more gasoline? In the following data set,

A. Write an equation in slope-intercept form that passes through (2,3) and is parallel to.

Correlation and Median-Median Line Statistics Test: Oct. 20 (Wednesday)

Chapter Nonlinear models. Objectives O Classify scatterplots O Use scatterplots and a graphing utility to find models for data and choose the model.

Results of mortality analyses, 1980 – 2003 years (Observed deaths: Obs; expected deaths: exp; Standardized Mortality Ratios: SMR) * statistically significant.

A little VOCAB.  Causation is the "causal relationship between conduct and result". That is to say that causation provides a means of connecting conduct.

Bar Graphs Used to compare amounts, or quantities The bars provide a visual display for a quick comparison between different categories.

Correlations: Linear Relationships Data What kind of measures are used? interval, ratio nominal Correlation Analysis: Pearson’s r (ordinal scales use Spearman’s.

Correlation & Linear Regression Using a TI-Nspire.

1 Objective Given two linearly correlated variables (x and y), find the linear function (equation) that best describes the trend. Section 10.3 Regression.

Fig. 2. Arterial fluorodeoxyglucose (FDG) uptake related to atherosclerosis. On positron emission tomography (PET) coronal (A), PET/CT fusion coronal (B),

Fig F-fluoride positron emission tomography (PET) in atherosclerosis

Fig year-old boy with Burkitt lymphoma. A

Fig. 2. Kaplan-Meier curves for survival in each breast cancer molecular subtype. Radiologic assessment in triple-negative breast cancer (A), HER2-positive.

Fig year-old girl with juvenile rheumatoid arthritis

Fig year-old man diagnosed with colon cancer with liver metastasis

Fig year-old man with lower legs numbness was diagnosed with severe canal stenosis at L3/4 and L4/5 and moderate canal stenosis at L2/3. A. MR myelography.

Fig. 4.Sagittal T1-weighted (A) and short tau inversion recovery (B) magnetic resonance images in 43-year-old woman with aneurysmal bone cyst of proximal.

Fig. 1. Images of 43-year-old woman with metastatic lung nodule from rectal cancer show round pulmonary nodule measuring 5 mm (arrows) in left basal lung.

Cautions about Correlation and Regression

Fig. 9. Visualization of aortic flow

Chapter 15 Linear Regression

Correlation and Regression-II

Investigating Relationships

Fig. 2. Pleural plaques in 75-year-old man who lived for 2 years within 1 km of asbestos mine 45 years ago and worked as construction worker for 30 years.

Using the two data sets below: 1) Draw a scatterplot for each.

Residuals Learning Target:

Fig. 1. Results of JAFROC analyses

Section 4.2 How Can We Define the Relationship between two

Linear Regression.

Linear regression Fitting a straight line to observations.

Simple Linear Regression

Correlation Coefficient

Regression Basics Tobias Econ 472.

Fig. 4. Mediastinal pleural plaques in asbestos-exposed individuals. A

Warm-Up 8/50 = /20 = /50 = .36 Math Social Studies P.E.

Residuals and Residual Plots

Analyzing the Relationship Between Two Variables

Regression making predictions

HW# : Complete the last slide

7.1 Draw Scatter Plots & Best-Fitting Lines

Performing a regression analysis

Correlation and Regression

Scatterplots line of best fit trend line interpolation extrapolation

Homework: PG. 204 #30, 31 pg. 212 #35,36 30.) a. Reading scores are predicted to increase by for each one-point increase in IQ. For x=90: 45.98;

Factor Analysis.

Fig. 2. 81-year-old man with colon cancer and hepatic metastasis: true negative case of CBCT virtual navigation-guided percutaneous pleural lesion biopsy.A. Pre-procedural.

Fig. 16. Spontaneous pulmonary hematoma and hemorrhage in a 54-year-old man.A. Initial CT image shows small bullae (arrow) in the right upper lobe. B. Follow-up.

Fig. 3. 47-year-old man with incidentally detected calcified lung nodule (arrows) on screening chest CT.Chest CT scans were reconstructed via six different.

ARTS AND WASL DATA SCHOOL DISTRICT LEVEL.

Fig. 4. Bland-Altman plots for assessment of agreement of fat-signal fraction (FF) between MR spectroscopy (MRS) and mapping image measurements. Bland-Altman.

Fig. 3. Structural equation modeling to estimate relationships among K-UCT and UAS7/CU-QoL/salivary cortisone levels. The K-UCT was found to be a significant.

Fig year-old man with chronic injuries of anterior talofibular ligament (ATFL) and anterior inferior tibiofibular ligament (AITFL). A. Axial fat.

Lung model expiratory CO2 (or PETOv2) representing simulated alveolar CO2 at baseline (no high-flow nasal cannula) and effect on expiratory CO2 at different.

CESD: Center for Epidemiologic Studies Depression.

Presentation transcript:

Fig. 5. Relationship between duration of asbestos exposure and maximum pleural plaque length in occupational and environmental asbestos exposure groups, visualized using locally weighted scatterplot smoothing regression fit modeling. Significant correlation was observed between asbestos exposure duration and maximum plaque length in occupational exposure group (p = 0.049) but not in environmental exposure group (p = 0.099). Fig. 5. Relationship between duration of asbestos exposure and maximum pleural plaque length in occupational and environmental asbestos exposure groups, visualized using locally weighted scatterplot smoothing regression fit modeling. Significant correlation was observed between asbestos exposure duration and maximum plaque length in occupational exposure group (p = 0.049) but . . . Korean J Radiol. 2015 Sep-Oct;16(5):1142-1152. http://dx.doi.org/10.3348/kjr.2015.16.5.1142