{"id":782,"date":"2023-07-28T18:44:38","date_gmt":"2023-07-28T18:44:38","guid":{"rendered":"https:\/\/statorials.org\/hi\/%e0%a4%a6%e0%a5%8d%e0%a4%b5%e0%a4%bf%e0%a4%98%e0%a4%be%e0%a4%a4-%e0%a4%aa%e0%a5%8d%e0%a4%b0%e0%a4%a4%e0%a4%bf%e0%a4%97%e0%a4%ae%e0%a4%a8-%e0%a4%86%e0%a4%b0\/"},"modified":"2023-07-28T18:44:38","modified_gmt":"2023-07-28T18:44:38","slug":"%e0%a4%a6%e0%a5%8d%e0%a4%b5%e0%a4%bf%e0%a4%98%e0%a4%be%e0%a4%a4-%e0%a4%aa%e0%a5%8d%e0%a4%b0%e0%a4%a4%e0%a4%bf%e0%a4%97%e0%a4%ae%e0%a4%a8-%e0%a4%86%e0%a4%b0","status":"publish","type":"post","link":"https:\/\/statorials.org\/hi\/%e0%a4%a6%e0%a5%8d%e0%a4%b5%e0%a4%bf%e0%a4%98%e0%a4%be%e0%a4%a4-%e0%a4%aa%e0%a5%8d%e0%a4%b0%e0%a4%a4%e0%a4%bf%e0%a4%97%e0%a4%ae%e0%a4%a8-%e0%a4%86%e0%a4%b0\/","title":{"rendered":"\u0906\u0930 \u092e\u0947\u0902 \u0926\u094d\u0935\u093f\u0918\u093e\u0924 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u0915\u0948\u0938\u0947 \u0915\u0930\u0947\u0902"},"content":{"rendered":"

<\/p>\n

\n

\u091c\u092c \u0926\u094b \u091a\u0930\u094b\u0902 \u092e\u0947\u0902 \u090f\u0915 \u0930\u0948\u0916\u093f\u0915 \u0938\u0902\u092c\u0902\u0927 \u0939\u094b\u0924\u093e \u0939\u0948, \u0924\u094b \u0939\u092e \u0905\u0915\u094d\u0938\u0930 \u0909\u0928\u0915\u0947 \u0938\u0902\u092c\u0902\u0927 \u0915\u094b \u092e\u093e\u092a\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0938\u0930\u0932 \u0930\u0948\u0916\u093f\u0915 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u0915\u093e<\/a> \u0909\u092a\u092f\u094b\u0917 \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902\u0964<\/span> <\/p>\n

\"\u0930\u0948\u0916\u093f\u0915<\/p>\n

\u0939\u093e\u0932\u093e\u0901\u0915\u093f, \u091c\u092c \u0926\u094b \u091a\u0930\u094b\u0902 \u092e\u0947\u0902 \u0926\u094d\u0935\u093f\u0918\u093e\u0924 \u0938\u0902\u092c\u0902\u0927 \u0939\u094b\u0924\u093e \u0939\u0948, \u0924\u094b \u0939\u092e \u0909\u0928\u0915\u0947 \u0938\u0902\u092c\u0902\u0927 \u0915\u094b \u092e\u093e\u092a\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0926\u094d\u0935\u093f\u0918\u093e\u0924 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u0915\u093e<\/strong> \u0909\u092a\u092f\u094b\u0917 \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902\u0964<\/span> <\/p>\n

\"\u0926\u094d\u0935\u093f\u0918\u093e\u0924<\/p>\n

\u092f\u0939 \u091f\u094d\u092f\u0942\u091f\u094b\u0930\u093f\u092f\u0932 \u092c\u0924\u093e\u0924\u093e \u0939\u0948 \u0915\u093f \u0906\u0930 \u092e\u0947\u0902 \u0926\u094d\u0935\u093f\u0918\u093e\u0924 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u0915\u0948\u0938\u0947 \u0915\u0930\u0947\u0902\u0964<\/span><\/p>\n

\u0909\u0926\u093e\u0939\u0930\u0923: \u0906\u0930 \u092e\u0947\u0902 \u0926\u094d\u0935\u093f\u0918\u093e\u0924 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928<\/strong><\/h3>\n

\u092e\u093e\u0928 \u0932\u0940\u091c\u093f\u090f \u0939\u092e \u0915\u093e\u092e \u0915\u093f\u090f \u0917\u090f \u0918\u0902\u091f\u094b\u0902 \u0915\u0940 \u0938\u0902\u0916\u094d\u092f\u093e \u0914\u0930 \u0930\u093f\u092a\u094b\u0930\u094d\u091f \u0915\u0940 \u0917\u0908 \u0916\u0941\u0936\u0940 \u0915\u0947 \u092c\u0940\u091a \u0938\u0902\u092c\u0902\u0927 \u0915\u094b \u0938\u092e\u091d\u0928\u093e \u091a\u093e\u0939\u0924\u0947 \u0939\u0948\u0902\u0964 \u0939\u092e\u093e\u0930\u0947 \u092a\u093e\u0938 11 \u0905\u0932\u0917-\u0905\u0932\u0917 \u0932\u094b\u0917\u094b\u0902 \u0915\u0947 \u0932\u093f\u090f \u092a\u094d\u0930\u0924\u093f \u0938\u092a\u094d\u0924\u093e\u0939 \u0915\u093e\u092e \u0915\u093f\u090f \u0917\u090f \u0918\u0902\u091f\u094b\u0902 \u0915\u0940 \u0938\u0902\u0916\u094d\u092f\u093e \u0914\u0930 \u0916\u0941\u0936\u0940 \u0915\u0947 \u0930\u093f\u092a\u094b\u0930\u094d\u091f \u0915\u093f\u090f \u0917\u090f \u0938\u094d\u0924\u0930 (0 \u0938\u0947 100 \u0915\u0947 \u092a\u0948\u092e\u093e\u0928\u0947 \u092a\u0930) \u092a\u0930 \u0928\u093f\u092e\u094d\u0928\u0932\u093f\u0916\u093f\u0924 \u0921\u0947\u091f\u093e \u0939\u0948:<\/span> <\/p>\n

\"\"<\/p>\n

R \u092e\u0947\u0902 \u0926\u094d\u0935\u093f\u0918\u093e\u0924 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u092e\u0949\u0921\u0932 \u0915\u094b \u092b\u093f\u091f \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0928\u093f\u092e\u094d\u0928\u0932\u093f\u0916\u093f\u0924 \u091a\u0930\u0923\u094b\u0902 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0947\u0902\u0964<\/span><\/p>\n

\u091a\u0930\u0923 1: \u0921\u0947\u091f\u093e \u0926\u0930\u094d\u091c \u0915\u0930\u0947\u0902.<\/strong><\/span><\/p>\n

\u0938\u092c\u0938\u0947 \u092a\u0939\u0932\u0947, \u0939\u092e \u090f\u0915 \u0921\u0947\u091f\u093e \u092b\u093c\u094d\u0930\u0947\u092e \u092c\u0928\u093e\u090f\u0902\u0917\u0947 \u091c\u093f\u0938\u092e\u0947\u0902 \u0939\u092e\u093e\u0930\u093e \u0921\u0947\u091f\u093e \u0939\u094b\u0917\u093e:<\/span><\/p>\n

 #createdata<\/span>\ndata <- data.frame(hours=c(6, 9, 12, 14, 30, 35, 40, 47, 51, 55, 60),\n                   happiness=c(14, 28, 50, 70, 89, 94, 90, 75, 59, 44, 27))\n\n#viewdata<\/span> \ndata\n\n   hours happiness\n1 6 14\n2 9 28\n3 12 50\n4 14 70\n5 30 89\n6 35 94\n7 40 90\n8 47 75\n9 51 59\n10 55 44\n11 60 27\n<\/strong><\/pre>\n
 \u091a\u0930\u0923 2: \u0921\u0947\u091f\u093e \u0915\u094b \u0935\u093f\u091c\u093c\u0941\u0905\u0932\u093e\u0907\u091c\u093c \u0915\u0930\u0947\u0902\u0964<\/strong><\/span><\/p>\n
 \u0907\u0938\u0915\u0947 \u092c\u093e\u0926, \u0939\u092e \u0921\u0947\u091f\u093e \u0915\u0940 \u0915\u0932\u094d\u092a\u0928\u093e \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u090f\u0915 \u0938\u0930\u0932 \u0938\u094d\u0915\u0948\u091f\u0930\u092a\u094d\u0932\u0949\u091f \u092c\u0928\u093e\u090f\u0902\u0917\u0947\u0964<\/span> <\/p>\n
 #create scatterplot<\/span>\nplot(data$hours, data$happiness, pch=16)<\/strong> <\/pre>\n
\"\u0906\u0930<\/p>\n
 \u0939\u092e \u0938\u094d\u092a\u0937\u094d\u091f \u0930\u0942\u092a \u0938\u0947 \u0926\u0947\u0916 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902 \u0915\u093f \u0921\u0947\u091f\u093e \u090f\u0915 \u0930\u0948\u0916\u093f\u0915 \u092a\u0948\u091f\u0930\u094d\u0928 \u0915\u093e \u092a\u093e\u0932\u0928 \u0928\u0939\u0940\u0902 \u0915\u0930\u0924\u093e \u0939\u0948\u0964<\/span><\/p>\n
 \u091a\u0930\u0923 3: \u090f\u0915 \u0938\u0930\u0932 \u0930\u0948\u0916\u093f\u0915 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u092e\u0949\u0921\u0932 \u092b\u093f\u091f \u0915\u0930\u0947\u0902\u0964<\/strong><\/span><\/p>\n
 \u0907\u0938\u0915\u0947 \u092c\u093e\u0926, \u0939\u092e \u092f\u0939 \u0926\u0947\u0916\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u090f\u0915 \u0938\u0930\u0932 \u0930\u0948\u0916\u093f\u0915 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u092e\u0949\u0921\u0932 \u092b\u093f\u091f \u0915\u0930\u0947\u0902\u0917\u0947 \u0915\u093f \u092f\u0939 \u0921\u0947\u091f\u093e \u092e\u0947\u0902 \u0915\u093f\u0924\u0928\u0940 \u0905\u091a\u094d\u091b\u0940 \u0924\u0930\u0939 \u092b\u093f\u091f \u092c\u0948\u0920\u0924\u093e \u0939\u0948:<\/span><\/p>\n
 #fit linear model<\/span>\nlinearModel <- lm(happiness ~ hours, data=data)\n\n#view model summary<\/span>\nsummary(linearModel)\n\nCall:\nlm(formula = happiness ~ hours)\n\nResiduals:\n   Min 1Q Median 3Q Max \n-39.34 -21.99 -2.03 23.50 35.11 \n\nCoefficients:\n            Estimate Std. Error t value Pr(>|t|)  \n(Intercept) 48.4531 17.3288 2.796 0.0208 *\nhours 0.2981 0.4599 0.648 0.5331  \n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n\nResidual standard error: 28.72 on 9 degrees of freedom\nMultiple R-squared: 0.0446, Adjusted R-squared: -0.06156 \nF-statistic: 0.4201 on 1 and 9 DF, p-value: 0.5331\n<\/strong><\/pre>\n
 \u092e\u0949\u0921\u0932 \u0926\u094d\u0935\u093e\u0930\u093e \u092c\u0924\u093e\u0908 \u0917\u0908 \u0916\u0941\u0936\u0940 \u092e\u0947\u0902 \u0915\u0941\u0932 \u092d\u093f\u0928\u094d\u0928\u0924\u093e \u0915\u0947\u0935\u0932 4.46%<\/strong> \u0939\u0948, \u091c\u0948\u0938\u093e \u0915\u093f \u090f\u0915\u093e\u0927\u093f\u0915 \u0906\u0930-\u0935\u0930\u094d\u0917 \u092e\u093e\u0928 \u0926\u094d\u0935\u093e\u0930\u093e \u0926\u093f\u0916\u093e\u092f\u093e \u0917\u092f\u093e \u0939\u0948\u0964<\/span><\/p>\n
 \u091a\u0930\u0923 4: \u090f\u0915 \u0926\u094d\u0935\u093f\u0918\u093e\u0924 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u092e\u0949\u0921\u0932 \u092b\u093f\u091f \u0915\u0930\u0947\u0902\u0964<\/strong><\/span><\/p>\n
 \u0907\u0938\u0915\u0947 \u092c\u093e\u0926, \u0939\u092e \u090f\u0915 \u0926\u094d\u0935\u093f\u0918\u093e\u0924 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u092e\u0949\u0921\u0932 \u092b\u093f\u091f \u0915\u0930\u0947\u0902\u0917\u0947\u0964<\/span><\/p>\n
 #create a new variable for hours 2<\/sup><\/span>\ndata$hours2 <- data$hours^2\n\n#fit quadratic regression model<\/span>\nquadraticModel <- lm(happiness ~ hours + hours2, data=data)\n\n#view model summary\n<\/span>summary(quadraticModel)\n\nCall:\nlm(formula = happiness ~ hours + hours2, data = data)\n\nResiduals:\n    Min 1Q Median 3Q Max \n-6.2484 -3.7429 -0.1812 1.1464 13.6678 \n\nCoefficients:\n             Estimate Std. Error t value Pr(>|t|)    \n(Intercept) -18.25364 6.18507 -2.951 0.0184 *  \nhours 6.74436 0.48551 13.891 6.98e-07 ***\nhours2 -0.10120 0.00746 -13.565 8.38e-07 ***\n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n\nResidual standard error: 6.218 on 8 degrees of freedom\nMultiple R-squared: 0.9602, Adjusted R-squared: 0.9502 \nF-statistic: 96.49 on 2 and 8 DF, p-value: 2.51e-06\n<\/strong><\/pre>\n
 \u092e\u0949\u0921\u0932 \u0926\u094d\u0935\u093e\u0930\u093e \u092c\u0924\u093e\u0908 \u0917\u0908 \u0916\u0941\u0936\u0940 \u092e\u0947\u0902 \u0915\u0941\u0932 \u0905\u0902\u0924\u0930 \u092c\u0922\u093c\u0915\u0930 96.02%<\/b> \u0939\u094b \u0917\u092f\u093e\u0964<\/span><\/p>\n
 \u0939\u092e \u092f\u0939 \u0926\u0947\u0916\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0928\u093f\u092e\u094d\u0928\u0932\u093f\u0916\u093f\u0924 \u0915\u094b\u0921 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902 \u0915\u093f \u092e\u0949\u0921\u0932 \u0921\u0947\u091f\u093e \u092e\u0947\u0902 \u0915\u093f\u0924\u0928\u0940 \u0905\u091a\u094d\u091b\u0940 \u0924\u0930\u0939 \u092b\u093f\u091f \u092c\u0948\u0920\u0924\u093e \u0939\u0948:<\/span> <\/p>\n
 #create sequence of hour values<\/span>\nhourValues <- seq(0, 60, 0.1)\n\n#create list of predicted happiness levels using quadratic model\n<\/span>happinessPredict <- predict(quadraticModel, list(hours=hourValues, hours2=hourValues^2))\n\n#create scatterplot of original data values\n<\/span>plot(data$hours, data$happiness, pch=16)\n#add predicted lines based on quadratic regression model<\/span>\nlines(hourValues, happinessPredict, col='blue')\n<\/strong><\/pre>\n
\"\u0906\u0930<\/p>\n
 \u0939\u092e \u0926\u0947\u0916 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902 \u0915\u093f \u0926\u094d\u0935\u093f\u0918\u093e\u0924 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u0930\u0947\u0916\u093e \u0921\u0947\u091f\u093e \u092e\u093e\u0928\u094b\u0902 \u0915\u094b \u0915\u093e\u092b\u0940 \u0905\u091a\u094d\u091b\u0940 \u0924\u0930\u0939 \u0938\u0947 \u092b\u093f\u091f \u0915\u0930\u0924\u0940 \u0939\u0948\u0964<\/span><\/p>\n
 \u091a\u0930\u0923 5: \u0926\u094d\u0935\u093f\u0918\u093e\u0924 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u092e\u0949\u0921\u0932 \u0915\u0940 \u0935\u094d\u092f\u093e\u0916\u094d\u092f\u093e \u0915\u0930\u0947\u0902\u0964<\/strong><\/span><\/p>\n
 \u092a\u093f\u091b\u0932\u0947 \u091a\u0930\u0923 \u092e\u0947\u0902, \u0939\u092e\u0928\u0947 \u0926\u0947\u0916\u093e \u0915\u093f \u0926\u094d\u0935\u093f\u0918\u093e\u0924 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u092e\u0949\u0921\u0932 \u0915\u093e \u092a\u0930\u093f\u0923\u093e\u092e \u0925\u093e:<\/span><\/p>\n
 Coefficients:\n             Estimate Std. Error t value Pr(>|t|)    \n(Intercept) -18.25364 6.18507 -2.951 0.0184 *  \nhours 6.74436 0.48551 13.891 6.98e-07 ***\nhours2 -0.10120 0.00746 -13.565 8.38e-07 ***\n<\/strong><\/pre>\n
 \u092f\u0939\u093e\u0902 \u092a\u094d\u0930\u0938\u094d\u0924\u0941\u0924 \u0917\u0941\u0923\u093e\u0902\u0915\u094b\u0902 \u0915\u0947 \u0906\u0927\u093e\u0930 \u092a\u0930, \u0938\u092e\u093e\u092f\u094b\u091c\u093f\u0924 \u0926\u094d\u0935\u093f\u0918\u093e\u0924 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u0939\u094b\u0917\u093e:<\/span><\/p>\n
 \u0916\u0941\u0936\u0940 = -0.1012 (\u0918\u0902\u091f\u0947) 2<\/sup> + 6.7444 (\u0918\u0902\u091f\u0947) – 18.2536<\/strong><\/span><\/p>\n
 \u0939\u092e \u0907\u0938 \u0938\u092e\u0940\u0915\u0930\u0923 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u093f\u0938\u0940 \u0935\u094d\u092f\u0915\u094d\u0924\u093f \u0915\u0940 \u0905\u0928\u0941\u092e\u093e\u0928\u093f\u0924 \u0916\u0941\u0936\u0940 \u0915\u093e \u092a\u0924\u093e \u0932\u0917\u093e\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902, \u092f\u0939 \u0926\u0947\u0916\u0924\u0947 \u0939\u0941\u090f \u0915\u093f \u0935\u0947 \u092a\u094d\u0930\u0924\u093f \u0938\u092a\u094d\u0924\u093e\u0939 \u0915\u093f\u0924\u0928\u0947 \u0918\u0902\u091f\u0947 \u0915\u093e\u092e \u0915\u0930\u0924\u0947 \u0939\u0948\u0902\u0964<\/span><\/p>\n
 \u0909\u0926\u093e\u0939\u0930\u0923 \u0915\u0947 \u0932\u093f\u090f, \u090f\u0915 \u0935\u094d\u092f\u0915\u094d\u0924\u093f \u091c\u094b \u092a\u094d\u0930\u0924\u093f \u0938\u092a\u094d\u0924\u093e\u0939 60 \u0918\u0902\u091f\u0947 \u0915\u093e\u092e \u0915\u0930\u0924\u093e \u0939\u0948 \u0909\u0938\u0915\u0940 \u0916\u0941\u0936\u0940 \u0915\u093e \u0938\u094d\u0924\u0930 22.09<\/strong> \u0939\u094b\u0917\u093e:<\/span><\/p>\n
 \u0916\u093c\u0941\u0936\u0940 = -0.1012(60) 2<\/sup> + 6.7444(60) \u2013 18.2536 = 22.09<\/span><\/p>\n
 \u0907\u0938\u0915\u0947 \u0935\u093f\u092a\u0930\u0940\u0924, \u091c\u094b \u0935\u094d\u092f\u0915\u094d\u0924\u093f \u092a\u094d\u0930\u0924\u093f \u0938\u092a\u094d\u0924\u093e\u0939 30 \u0918\u0902\u091f\u0947 \u0915\u093e\u092e \u0915\u0930\u0924\u093e \u0939\u0948 \u0909\u0938\u0915\u0940 \u0916\u0941\u0936\u0940 \u0915\u093e \u0938\u094d\u0924\u0930 92.99<\/strong> \u0939\u094b\u0928\u093e \u091a\u093e\u0939\u093f\u090f:<\/span><\/p>\n
 \u0916\u0941\u0936\u0940 = -0.1012(30) 2<\/sup> + 6.7444(30) \u2013 18.2536 = 92.99<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"
\u091c\u092c \u0926\u094b \u091a\u0930\u094b\u0902 \u092e\u0947\u0902 \u090f\u0915 \u0930\u0948\u0916\u093f\u0915 \u0938\u0902\u092c\u0902\u0927 \u0939\u094b\u0924\u093e \u0939\u0948, \u0924\u094b \u0939\u092e \u0905\u0915\u094d\u0938\u0930 \u0909\u0928\u0915\u0947 \u0938\u0902\u092c\u0902\u0927 \u0915\u094b \u092e\u093e\u092a\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0938\u0930\u0932 \u0930\u0948\u0916\u093f\u0915 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902\u0964 \u0939\u093e\u0932\u093e\u0901\u0915\u093f, \u091c\u092c \u0926\u094b \u091a\u0930\u094b\u0902 \u092e\u0947\u0902 \u0926\u094d\u0935\u093f\u0918\u093e\u0924 \u0938\u0902\u092c\u0902\u0927 \u0939\u094b\u0924\u093e \u0939\u0948, \u0924\u094b \u0939\u092e \u0909\u0928\u0915\u0947 \u0938\u0902\u092c\u0902\u0927 \u0915\u094b \u092e\u093e\u092a\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0926\u094d\u0935\u093f\u0918\u093e\u0924 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902\u0964 \u092f\u0939 \u091f\u094d\u092f\u0942\u091f\u094b\u0930\u093f\u092f\u0932 \u092c\u0924\u093e\u0924\u093e \u0939\u0948 \u0915\u093f […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"class_list":["post-782","post","type-post","status-publish","format-standard","hentry","category-3"],"yoast_head":"\n\u0906\u0930 - \u0938\u094d\u091f\u0947\u091f\u094b\u0932\u0949\u091c\u0940 \u092e\u0947\u0902 \u0926\u094d\u0935\u093f\u0918\u093e\u0924 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u0915\u0948\u0938\u0947 \u0915\u0930\u0947\u0902<\/title>\n<meta name=\"description\" content=\"\u091a\u0930\u0923-\u0926\u0930-\u091a\u0930\u0923 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\u092c\u0947\u0902\u091c\u093e\u092e\u093f\u0928 \u090f\u0902\u0921\u0930\u0938\u0928\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u0926\u094d\u0935\u093e\u0930\u093e \u0932\u093f\u0916\u093f\u0924\" \/>\n\t<meta name=\"twitter:data1\" content=\"\u0921\u0949. \u092c\u0947\u0902\u091c\u093e\u092e\u093f\u0928 \u090f\u0902\u0921\u0930\u0938\u0928\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u0905\u0928\u0941\u092e\u093e\u0928\u093f\u0924 \u092a\u0922\u093c\u0928\u0947 \u0915\u093e \u0938\u092e\u092f\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 \u092e\u093f\u0928\u091f\" \/>\n<script type=\"application\/ld+json\" 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