This study aims to find the correlation between the number of weeks of gestation and theweight of the baby at birth. The data consists of a sample of 15 births. It takes the numberof weeks of gestation as the x variable of the plot and the weight of the baby at birth as the yvariable. We are using MS Excel 2016 for analyzing this data. The data is as follows:Gest.P(we Wt (gm)3829403831303624203424503927603524404032264233013727294034103627153930953931303932443525201) What are the assumptions of a simple linear regression model.

In simple linear regression there will be only one independent variable. In multiple linear…

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1) What are the assumptions of a simple linear regression model.

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Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

This study aims to find the correlation between the number of weeks of gestation and the
weight of the baby at birth. The data consists of a sample of 15 births. It takes the number
of weeks of gestation as the x variable of the plot and the weight of the baby at birth as the y
variable. We are using MS Excel 2016 for analyzing this data. The data is as follows:
Gest.P(we Wt (gm)
38
2940
38
3130
36
2420
34
2450
39
2760
35
2440
40
3226
42
3301
37
2729
40
3410
36
2715
39
3095
39
3130
39
3244
35
2520
1) What are the assumptions of a simple linear regression model.

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Situation: The Ipod Touch has been out for two years now and a lot of data has been collected. Relevant Relationship: There is a functional relationship between Price of an IPod Touch,p and Weekly Demand, s. Below is a table of data that have been collected Price,p, ($) Weekly Demand, s, (1,000s) 150 170 190 210 230 250 A.. Find the linear model that best fits this data using regression and enter the model below (for entry round the linear parameter value to nearest 0.01 and constant parameter to nearest 1) S = T(p) 215 201 200 192 180 168 - B. The squared correlation coefficient ² was [Select an answer 0.95 (note: values less than 0.95 MAY mean the model is not appropriate for making predictions) Now answer these two questions using the UNROUNDED model parameters C. What does the model predict will be the weekly demand if the price of an ipod touch is $213? (nearest 100) D. According to the model at what should the price be set in order to have a weekly demand of 180,000 ipod Touches?…
In a simple linear regression equation, X is the----- variable.
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A 1 ROAA (%) Efficiency Ratio (%) 2 1.04 39.93 3 57.75 4 81.4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 0.68 7.27 1.08 0.72 0.92 0.79 1.04 1.76 1.07 1.37 0.93 0.66 1.72 1.5 0.59 2.12 1.11 1.45 1.06 B A 53.49 71.08 65.41 68.07 68.14 68.1 64.82 48.58 63.1 59.16 49.93 54.7 81.6 75.21 69.82 49.47 57.09 с Total Risk-Based Capital (%) 17.04 13.88 27.77 18.31 14.66 14.04 13.38 16.8 16.69 13.86 12 18.65 19.76 17.69 26.6 15.08 14.55 17.5 16.03 14.62 D E F G H |