diff --git a/apps/regression/calculation_controller.cpp b/apps/regression/calculation_controller.cpp
index 021760dc2..4d24c7c26 100644
--- a/apps/regression/calculation_controller.cpp
+++ b/apps/regression/calculation_controller.cpp
@@ -176,8 +176,8 @@ void CalculationController::willDisplayCellAtLocation(HighlightCell * cell, int
   const int numberSignificantDigits = Preferences::LargeNumberOfSignificantDigits;
   if (i > 0 && j > 0 && j <= k_totalNumberOfDoubleBufferRows) {
     ArgCalculPointer calculationMethods[k_totalNumberOfDoubleBufferRows] = {&Store::meanOfColumn, &Store::sumOfColumn, &Store::squaredValueSumOfColumn, &Store::standardDeviationOfColumn, &Store::varianceOfColumn};
-    double calculation1 = (m_store->*calculationMethods[j-1])(seriesNumber, 0);
-    double calculation2 = (m_store->*calculationMethods[j-1])(seriesNumber, 1);
+    double calculation1 = (m_store->*calculationMethods[j-1])(seriesNumber, 0, false);
+    double calculation2 = (m_store->*calculationMethods[j-1])(seriesNumber, 1, false);
     EvenOddDoubleBufferTextCellWithSeparator * myCell = (EvenOddDoubleBufferTextCellWithSeparator *)cell;
     constexpr int bufferSize = PrintFloat::charSizeForFloatsWithPrecision(numberSignificantDigits);
     char buffer[bufferSize];
@@ -196,8 +196,16 @@ void CalculationController::willDisplayCellAtLocation(HighlightCell * cell, int
   }
   if (i > 0 && j > k_totalNumberOfDoubleBufferRows && j < k_regressionCellIndex) {
     assert(j != k_regressionCellIndex);
-    CalculPointer calculationMethods[] = {&Store::doubleCastedNumberOfPairsOfSeries, &Store::covariance, &Store::columnProductSum};
-    double calculation = (m_store->*calculationMethods[j-k_totalNumberOfDoubleBufferRows-1])(seriesNumber);
+    double calculation = 0;
+    const int calculationIndex = j-k_totalNumberOfDoubleBufferRows-1;
+    if (calculationIndex == 0) {
+      calculation = m_store->doubleCastedNumberOfPairsOfSeries(seriesNumber);
+    } else if (calculationIndex == 1) {
+      calculation = m_store->covariance(seriesNumber);
+    } else {
+      assert(calculationIndex == 2);
+      calculation = m_store->columnProductSum(seriesNumber);
+   }
     constexpr int bufferSize = PrintFloat::charSizeForFloatsWithPrecision(numberSignificantDigits);
     char buffer[bufferSize];
     PoincareHelpers::ConvertFloatToText<double>(calculation, buffer, bufferSize, numberSignificantDigits);
@@ -228,8 +236,8 @@ void CalculationController::willDisplayCellAtLocation(HighlightCell * cell, int
     if (j > k_regressionCellIndex + maxNumberCoefficients) {
       // Fill r and r2 if needed
       if (modelType == Model::Type::Linear) {
-        CalculPointer calculationMethods[2] = {&Store::correlationCoefficient, &Store::squaredCorrelationCoefficient};
-        double calculation = (m_store->*calculationMethods[j - k_regressionCellIndex - maxNumberCoefficients - 1])(seriesNumber);
+        const int calculationIndex = j - k_regressionCellIndex - maxNumberCoefficients - 1;
+        double calculation = calculationIndex == 0 ? m_store->correlationCoefficient(seriesNumber) : m_store->squaredCorrelationCoefficient(seriesNumber);
         constexpr int bufferSize = PrintFloat::charSizeForFloatsWithPrecision(numberSignificantDigits);
         char buffer[bufferSize];
         PoincareHelpers::ConvertFloatToText<double>(calculation, buffer, bufferSize, numberSignificantDigits);
diff --git a/apps/regression/model/linear_model.h b/apps/regression/model/linear_model.h
index 6f1c91153..4fd9d2988 100644
--- a/apps/regression/model/linear_model.h
+++ b/apps/regression/model/linear_model.h
@@ -12,7 +12,7 @@ public:
   I18n::Message formulaMessage() const override { return I18n::Message::LinearRegressionFormula; }
   double evaluate(double * modelCoefficients, double x) const override;
   double levelSet(double * modelCoefficients, double xMin, double step, double xMax, double y, Poincare::Context * context) override;
-  virtual void fit(Store * store, int series, double * modelCoefficients, Poincare::Context * context) override;
+  void fit(Store * store, int series, double * modelCoefficients, Poincare::Context * context) override;
   double partialDerivate(double * modelCoefficients, int derivateCoefficientIndex, double x) const override;
   int numberOfCoefficients() const override { return 2; }
   int bannerLinesCount() const override { return 3; }
diff --git a/apps/regression/model/power_model.cpp b/apps/regression/model/power_model.cpp
index 928e25514..c152c9c1d 100644
--- a/apps/regression/model/power_model.cpp
+++ b/apps/regression/model/power_model.cpp
@@ -61,6 +61,12 @@ double PowerModel::partialDerivate(double * modelCoefficients, int derivateCoeff
   return 0.0;
 }
 
+void PowerModel::fit(Store * store, int series, double * modelCoefficients, Poincare::Context * context) {
+  /* Y1 = aX1^b => ln(Y1) = ln(a) + b*ln(X1)*/
+  modelCoefficients[0] = exp(store->yIntercept(series, true));
+  modelCoefficients[1] = store->slope(series, true);
+}
+
 bool PowerModel::dataSuitableForFit(Store * store, int series) const {
   if (!Model::dataSuitableForFit(store, series)) {
     return false;
diff --git a/apps/regression/model/power_model.h b/apps/regression/model/power_model.h
index ac544e5c1..638467386 100644
--- a/apps/regression/model/power_model.h
+++ b/apps/regression/model/power_model.h
@@ -13,10 +13,11 @@ public:
   double evaluate(double * modelCoefficients, double x) const override;
   double levelSet(double * modelCoefficients, double xMin, double step, double xMax, double y, Poincare::Context * context) override;
   double partialDerivate(double * modelCoefficients, int derivateCoefficientIndex, double x) const override;
+  void fit(Store * store, int series, double * modelCoefficients, Poincare::Context * context) override;
   int numberOfCoefficients() const override { return 2; }
   int bannerLinesCount() const override { return 2; }
 protected:
-  virtual bool dataSuitableForFit(Store * store, int series) const override;
+  bool dataSuitableForFit(Store * store, int series) const override;
 };
 
 }
diff --git a/apps/regression/store.cpp b/apps/regression/store.cpp
index ceba3633a..0afd7941a 100644
--- a/apps/regression/store.cpp
+++ b/apps/regression/store.cpp
@@ -204,45 +204,53 @@ float Store::minValueOfColumn(int series, int i) const {
   return minColumn;
 }
 
-double Store::squaredValueSumOfColumn(int series, int i) const {
+double Store::squaredValueSumOfColumn(int series, int i, bool lnOfSeries) const {
   double result = 0;
   for (int k = 0; k < numberOfPairsOfSeries(series); k++) {
-    result += m_data[series][i][k]*m_data[series][i][k];
+    if (lnOfSeries) {
+      result += log(m_data[series][i][k]) * log(m_data[series][i][k]);
+    } else {
+      result += m_data[series][i][k]*m_data[series][i][k];
+    }
   }
   return result;
 }
 
-double Store::columnProductSum(int series) const {
+double Store::columnProductSum(int series, bool lnOfSeries) const {
   double result = 0;
   for (int k = 0; k < numberOfPairsOfSeries(series); k++) {
-    result += m_data[series][0][k]*m_data[series][1][k];
+    if (lnOfSeries) {
+      result += log(m_data[series][0][k]) * log(m_data[series][1][k]);
+    } else {
+      result += m_data[series][0][k] * m_data[series][1][k];
+    }
   }
   return result;
 }
 
-double Store::meanOfColumn(int series, int i) const {
-  return numberOfPairsOfSeries(series) == 0 ? 0 : sumOfColumn(series, i)/numberOfPairsOfSeries(series);
+double Store::meanOfColumn(int series, int i, bool lnOfSeries) const {
+  return numberOfPairsOfSeries(series) == 0 ? 0 : sumOfColumn(series, i, lnOfSeries)/numberOfPairsOfSeries(series);
 }
 
-double Store::varianceOfColumn(int series, int i) const {
-  double mean = meanOfColumn(series, i);
-  return squaredValueSumOfColumn(series, i)/numberOfPairsOfSeries(series) - mean*mean;
+double Store::varianceOfColumn(int series, int i, bool lnOfSeries) const {
+  double mean = meanOfColumn(series, i, lnOfSeries);
+  return squaredValueSumOfColumn(series, i, lnOfSeries)/numberOfPairsOfSeries(series) - mean*mean;
 }
 
-double Store::standardDeviationOfColumn(int series, int i) const {
-  return std::sqrt(varianceOfColumn(series, i));
+double Store::standardDeviationOfColumn(int series, int i, bool lnOfSeries) const {
+  return std::sqrt(varianceOfColumn(series, i, lnOfSeries));
 }
 
-double Store::covariance(int series) const {
-  return columnProductSum(series)/numberOfPairsOfSeries(series) - meanOfColumn(series, 0)*meanOfColumn(series, 1);
+double Store::covariance(int series, bool lnOfSeries) const {
+  return columnProductSum(series, lnOfSeries)/numberOfPairsOfSeries(series) - meanOfColumn(series, 0, lnOfSeries)*meanOfColumn(series, 1, lnOfSeries);
 }
 
-double Store::slope(int series) const {
-  return LinearModelHelper::Slope(covariance(series), varianceOfColumn(series, 0));
+double Store::slope(int series, bool lnOfSeries) const {
+  return LinearModelHelper::Slope(covariance(series, lnOfSeries), varianceOfColumn(series, 0, lnOfSeries));
 }
 
-double Store::yIntercept(int series) const {
-  return LinearModelHelper::YIntercept(meanOfColumn(series, 1), meanOfColumn(series, 0), slope(series));
+double Store::yIntercept(int series, bool lnOfSeries) const {
+  return LinearModelHelper::YIntercept(meanOfColumn(series, 1, lnOfSeries), meanOfColumn(series, 0, lnOfSeries), slope(series, lnOfSeries));
 }
 
 double Store::yValueForXValue(int series, double x, Poincare::Context * globalContext) {
diff --git a/apps/regression/store.h b/apps/regression/store.h
index da5a24252..dfdc682c1 100644
--- a/apps/regression/store.h
+++ b/apps/regression/store.h
@@ -56,14 +56,14 @@ public:
   // Calculation
   double * coefficientsForSeries(int series, Poincare::Context * globalContext);
   double doubleCastedNumberOfPairsOfSeries(int series) const;
-  double squaredValueSumOfColumn(int series, int i) const;
-  double columnProductSum(int series) const;
-  double meanOfColumn(int series, int i) const;
-  double varianceOfColumn(int series, int i) const;
-  double standardDeviationOfColumn(int series, int i) const;
-  double covariance(int series) const;
-  double slope(int series) const;
-  double yIntercept(int series) const;
+  double squaredValueSumOfColumn(int series, int i, bool lnOfSeries = false) const;
+  double columnProductSum(int series, bool lnOfSeries = false) const;
+  double meanOfColumn(int series, int i, bool lnOfSeries = false) const;
+  double varianceOfColumn(int series, int i, bool lnOfSeries = false) const;
+  double standardDeviationOfColumn(int series, int i, bool lnOfSeries = false) const;
+  double covariance(int series, bool lnOfSeries = false) const;
+  double slope(int series, bool lnOfSeries = false) const;
+  double yIntercept(int series, bool lnOfSeries = false) const;
   double yValueForXValue(int series, double x, Poincare::Context * globalContext);
   double xValueForYValue(int series, double y, Poincare::Context * globalContext);
   double correlationCoefficient(int series) const;
@@ -89,8 +89,7 @@ private:
   Poincare::Preferences::AngleUnit m_angleUnit;
 };
 
-typedef double (Store::*ArgCalculPointer)(int, int) const;
-typedef double (Store::*CalculPointer)(int) const;
+typedef double (Store::*ArgCalculPointer)(int, int, bool) const;
 typedef void (Store::*RangeMethodPointer)();
 
 }
diff --git a/apps/shared/double_pair_store.cpp b/apps/shared/double_pair_store.cpp
index d298aa21b..b35c56de7 100644
--- a/apps/shared/double_pair_store.cpp
+++ b/apps/shared/double_pair_store.cpp
@@ -98,12 +98,12 @@ int DoublePairStore::indexOfKthNonEmptySeries(int k) const {
   return 0;
 }
 
-double DoublePairStore::sumOfColumn(int series, int i) const {
+double DoublePairStore::sumOfColumn(int series, int i, bool lnOfSeries) const {
   assert(series >= 0 && series < k_numberOfSeries);
   assert(i == 0 || i == 1);
   double result = 0;
   for (int k = 0; k < m_numberOfPairs[series]; k++) {
-    result += m_data[series][i][k];
+    result += lnOfSeries ? log(m_data[series][i][k]) : m_data[series][i][k];
   }
   return result;
 }
diff --git a/apps/shared/double_pair_store.h b/apps/shared/double_pair_store.h
index 465b78a9d..9c8859612 100644
--- a/apps/shared/double_pair_store.h
+++ b/apps/shared/double_pair_store.h
@@ -47,7 +47,7 @@ public:
   int indexOfKthNonEmptySeries(int k) const;
 
   // Calculations
-  double sumOfColumn(int series, int i) const;
+  double sumOfColumn(int series, int i, bool lnOfSeries = false) const;
   bool seriesNumberOfAbscissaeGreaterOrEqualTo(int series, int i) const;
   uint32_t storeChecksum() const;
   uint32_t storeChecksumForSeries(int series) const;