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Fiesta28 [93]
3 years ago
7

Helllllp >_< Compare: 1.2057 O 1.1421

Mathematics
1 answer:
vladimir2022 [97]3 years ago
6 0

Answer:

Widal Kit Salmonella Ha, Hb, Hc, Hd, OA, OB, OC, OD

Rapid Labs Widal antigen set contains ready to use concentrated smooth antigen suspensions of the bacilli; S. typhi ‘O’. S. typhi ‘H’. S, paratyphi ‘AO’. S. paratyphi ’BO‘. S. paratyphi ’AH’, S. paratyphi ‘BH’. S. paratyphi ‘CH’. S. paratyphi ‘CO’ and/or polyspecific positive control reactive with these antigens.

When the Widal antigen suspensions are mixed and incubated with the patient’s serum, anti salmonella antibodies present in the patient serum react with the antigen suspensions to give agglutination. Agglutination is a positive test result, indicating presence of anti-salmonella antibodies in the patient serum. No agglutination is a negative test result indicating absence of anti-salmonella antibodies.

Pack size – 8 x 5ml

This kit does NOT contain positive and negative controls

Widal Kit Salmonella Ha, Hb, Hc, Hd, OA, OB, OC, OD

Rapid Labs Widal antigen set contains ready to use concentrated smooth antigen suspensions of the bacilli; S. typhi ‘O’. S. typhi ‘H’. S, paratyphi ‘AO’. S. paratyphi ’BO‘. S. paratyphi ’AH’, S. paratyphi ‘BH’. S. paratyphi ‘CH’. S. paratyphi ‘CO’ and/or polyspecific positive control reactive with these antigens.

When the Widal antigen suspensions are mixed and incubated with the patient’s serum, anti salmonella antibodies present in the patient serum react with the antigen suspensions to give agglutination. Agglutination is a positive test result, indicating presence of anti-salmonella antibodies in the patient serum. No agglutination is a negative test result indicating absence of anti-salmonella antibodies.

Pack size – 8 x 5ml

This kit does NOT contain positive and negative control

Step-by-step explanation:

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. The estimate regression equation for a model involving two independent variables and 10 observations follows.y = 29.1270 + 0.5
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Answer:

b) y = 289.815 when x_1 = 180 \text{ and } x_2 = 310

Step-by-step explanation:

We are given the following information in the question:

y = 29.1270 + 0.5906x_1 + 0.4980x_2

where y is the dependent variable,

x_1, x_2 are the independent variable.

The multiple regression equation is of the form:

y = b_0 + b_1x_1 + b_2x_2

where,

b_0: is the intercept of the equation and is the value of dependent variable when all the independent variable are zero.

b_1: It is the slope coefficient of the independent variable x_1.

b_2: It is the slope coefficient of the independent variable x_2.

  • The regression coefficient in multiple regression is the slope of the linear relationship between the dependent and the part of a predictor variable that is independent of all other predictor variables.

Comparing the equations, we get:

b_1 = 0.5906\\b_2 = 0.4980

  • This means holding x_2 constant, a change of one in x_1 is associated with a change of 0.5906 in the dependent variable.
  • This means holding x_1 constant, a change of 1 in x_2 is associated with a change of 0.4980 in the dependent variable.

b) We have to estimate the value of y

y = 29.1270 + 0.5906(180) + 0.4980(310) = 289.815

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